PhD in Computational Science

2024/2025

Quality assurance

The UDC International Doctoral School (EIDUDC) is subject to an Internal Quality Assurance System (IQAS) which governs all UDC PhD programmes ratified by Royal Decree-Law 99/2011, in compliance with EU Standards and Guidelines for Quality Assurance in the EHEA. For more information, see documentation relating to the UDC International Doctoral School Internal Quality Assurance System (Regulations for the implementation and administration of the International Doctoral School SGIC for UDC PhD programmes ratified under RD 99/2011; International Doctoral School IQAS Manual; International Doctoral School IQASProcedures).

Guidelines for the monitoring and supervision of the student learning process and outcomes are established in the IQAS Procedures document. The bodies and mechanisms responsible for the coordination, evaluation and continuous improvement of the programme of study are as follows:

Academic Committee for PhD Programmes (CAPD): university body responsible for the academic coordination of PhD programmes and academic decisions regarding PhD degree and degree candidates. The CAPD establishes the guidelines and procedures for the programme coordinator and all individuals involved in the degree. A UDC coordinator is appointed for all UDC PhD programmes ratified under RD 99/2011, including inter-university programmes operated by partner universities.

EIDUDC Quality Assurance Committee (CGC): body responsible for formulating and monitoring the SGIC and PhD degree programmes. The CGC also fulfils an internal communication role within the EIDUDC in relation to its objectives, plans, programmes and responsibilities. An annual monitoring report is produced by the EIDUDC Permanent Committee, acting in the name of the CGC.

Learning outcomes

The International Doctoral School IQAS sets out the standards and indicators applied by Academic Committees in relation to UDC PhD programmes for the measurement and analysis of learning outcomes and academic standards.

These indicators include the number of doctoral theses defended, ‘International Doctorate’ certifications awarded, PhDs completed within the published time scale (3-4 years), PhDs awarded and PhDs abandoned, in addition to the average timescale for completion of the degree.

Quality assurance

To ensure that the title is developed in accordance with the verification report presented the center conducts an annual monitoring report in accordance with the procedures of the center IQAS and results. This report is reviewed by the ACSUG, external evaluation agency.

The outcome of this analysis will emerge corrective actions and improvement proposals that achieve the intended objectives and the improvement of the degree.

Quality regulation

Committees

In order to ensure proper standards and quality at UDC, a specific academic management committee of the PhD programme will be established.

Academic committee

Santos Reyes, José
Coordinador

Cabalar Fernández, José Pedro
Secretario

Alonso Pardo, Miguel Ángel
Vocal PDI

Alonso Betanzos, María Amparo
Vocal PDI

Paramá Gabía, José Ramón
Vocal PDI

Duro Fernández, Richard José
Vocal PDI

Valderruten Vidal, Alberto
Vocal PDI

Program tracking facts

	Period	Value
Places offered Number of places for new students entering PhD (IPD01)	2023/2024	20
Demand Number of applicants for PhD admission (IPD02)	2023/2024	15
First-time enrollment Number of first-time enrollment students in PhD (IPD03)	2023/2024	10
First-time enrollment by adaptation Number of first-time enrollment students in the program or students coming from other studies in extinction (IPD03.1)	2023/2024	0
Total enrollment Total number of students enrolled (IPD04)	2023/2024	56
First-time enrollment coming from other universities Ratio between the number of first-time enrolled students coming from other universities and the total number of first-time enrolled students in the program (IPD05)	2023/2024	50
Percentage of foreign students Ratio between the number of foreign students enrolled and the total number of students enrolled in the programme (IPD06)	2023/2024	16.07
Percentage of first-time enrolled students who need training complements Ratio between the number of students enrolled who need training complements and the total number of new students enrolled in the programme (IPD07)	2023/2024	0
Percentage of full-time enrollees Ratio between the number of students under full time status and the number of students enrolled in the programme (IPD08.1)	2023/2024	75
Percentage of partial-time enrollees Ratio between the number of students under half time status and the number of students enrolled in the programme (IPD08.2)	2023/2024	16.07
Percentage of enrollees under mixed status Ratio between the number of students under mixed status and the number of students enrolled in the programme (IPD08.3)	2023/2024	8.93
Percentage of enrollees who carried out a stay passed by the CAPD (Outgoing) Ratio between the number of students who carried out a stay as visiting researchers passed by the CAPD (outgoing students) and the total number of students enrolled in the programme (IPD09.1)	2023/2024	12.5
Percentage of enrollees who carried out a stay passed by the CAPD at UDC (Incoming) Number of students who carried out a stay as visiting researchers passed by the CAPD (incoming students) (IPD09.2)	2023/2024	n/a
Percentage of enrollees with a grant or pre-doctoral contract Ratio between the number of students with a grant or pre-doctoral contract and the number of students enrolled in the programme (IPD11)	2023/2024	33.93
Percentage of theses defended by students who had several directors Ratio between the number of theses defended by students of the programme who had several directors and the total number of defended theses in the programme (IPD14)	2023/2024	100
Percentage of examination board members coming from an foreign institution Ratio between the number of examination board members of thesis linked to the programme coming from an foreign institution and the total umber of examination board members of thesis linked to the programme (IPD17)	2023/2024	28.57
Total number of defended thesis Total number of defended thesis linked to the programme (IPD18.1)	2023/2024	5
Percentage of defended thesis written by full-time students Ratio between the total number of defended thesis written by students under full time status and the total number of defended theses in the programme (IPD18.2.1)	2023/2024	100
Percentage of defended thesis written by partial-time students Ratio between the total number of defended thesis written by students under partial time status and the total number of defended theses in the programme (IPD18.2.2)	2023/2024	0
Percentage of defended thesis written by students under mixed status Ratio between the total number of defended thesis written by students under mixed status and the total number of defended theses in the programme (IPD18.2.3)	2023/2024	0
Total number of tesis written in Galician Total number of defended thesis linked to the programme written in Galician (IPD18.3.1)	2023/2024	0
Total number of tesis written in Spanish Total number of defended thesis linked to the programme written in Spanish (IPD18.3.2)	2023/2024	0
Total number of tesis written in other languages Total number of defended thesis linked to the programme written in other languages (IPD18.3.3)	2023/2024	5
Average duration of studies of full-time students Average duration of studies for students under full time status who defended a thesis (in days) (IPD18.4.1)	2023/2024	1,445
Average duration of studies of partial-time students Average duration of studies for students under half time status who defended a thesis (in days) (IPD18.4.2)	2023/2024	n/a
Average duration of studies of students under mixed time status Average duration of studies for students under mixed time status who defended a thesis (in days) (IPD18.4.3)	2023/2024	n/a
Success rate. Percentage of students who defended their theses without asking for an extension Ratio between the number of doctoral students who defended their theses without asking for an extension and the total number of defended thesis linked to the programme (IPD18.5.1)	2023/2024	0
Success rate. Percentage of students who defended their theses after asking for the first extension Ratio between the number of doctoral students who defended their theses after asking for the first extension and the total number of defended thesis linked to the programme (IPD18.5.2)	2023/2024	80
Success rate. Percentage of students who defended their theses after asking for the second extension Ratio between the number of doctoral students who defended their theses after asking for the second extension and the total number of defended thesis linked to the programme (IPD18.5.3)	2023/2024	20
Percentage of "cum laude" theses Ratio between the number of defended theses linked to the programme with "Cum Laude" qualification and the total number of defended thesis linked to the programme (IPD18.6)	2023/2024	100
Percentage of theses with International Component Ratio between the number of defended theses linked to the programme with International Component and the total number of defended thesis linked to the programme (IPD18.7)	2023/2024	80
Dropout rate Ratio between the number of doctoral students who cause permanent withdrawal from the X course and the total number of doctoral students who could re-enroll in this programme. (IPDx21)	2023/2024	6.67
Tasa de ocupación Relación porcentual entre el nº de estudantes de nuevo ingreso y el nº de plazas ofertadas. (D03-P01-I01)	2023/2024	50
Tasa de demanda Relación numérica entre el nº de solicitudes de admisión y el nº de plazas ofertadas. (D03-P01-I02)	2023/2024	0.75
Porcentaje de tesis con mención industrial Relación porcentual entre el nº de tesis defendidas con mención industrial y el nº total de tesis defendidas (valor acumulativo). (D04-P01-I08)	2023/2024	0.38
Porcentaje de tesis defendidas en cotutela Relación porcentual entre el nº de tesis defendidas en cotutela y el nº total de tesis defendidas. (D04-P01-I11)	2023/2024	0

	Period	Value
Places offered Number of places for new students entering PhD (IPD01)	2022/2023	20
Demand Number of applicants for PhD admission (IPD02)	2022/2023	15
First-time enrollment Number of first-time enrollment students in PhD (IPD03)	2022/2023	12
First-time enrollment by adaptation Number of first-time enrollment students in the program or students coming from other studies in extinction (IPD03.1)	2022/2023	0
Total enrollment Total number of students enrolled (IPD04)	2022/2023	54
First-time enrollment coming from other universities Ratio between the number of first-time enrolled students coming from other universities and the total number of first-time enrolled students in the program (IPD05)	2022/2023	33.33
Percentage of foreign students Ratio between the number of foreign students enrolled and the total number of students enrolled in the programme (IPD06)	2022/2023	12.96
Percentage of first-time enrolled students who need training complements Ratio between the number of students enrolled who need training complements and the total number of new students enrolled in the programme (IPD07)	2022/2023	0
Percentage of full-time enrollees Ratio between the number of students under full time status and the number of students enrolled in the programme (IPD08.1)	2022/2023	72.22
Percentage of partial-time enrollees Ratio between the number of students under half time status and the number of students enrolled in the programme (IPD08.2)	2022/2023	20.37
Percentage of enrollees under mixed status Ratio between the number of students under mixed status and the number of students enrolled in the programme (IPD08.3)	2022/2023	7.41
Percentage of enrollees who carried out a stay passed by the CAPD (Outgoing) Ratio between the number of students who carried out a stay as visiting researchers passed by the CAPD (outgoing students) and the total number of students enrolled in the programme (IPD09.1)	2022/2023	1.85
Percentage of enrollees who carried out a stay passed by the CAPD at UDC (Incoming) Number of students who carried out a stay as visiting researchers passed by the CAPD (incoming students) (IPD09.2)	2022/2023	n/a
Percentage of enrollees with a grant or pre-doctoral contract Ratio between the number of students with a grant or pre-doctoral contract and the number of students enrolled in the programme (IPD11)	2022/2023	25.93
Percentage of theses defended by students who had several directors Ratio between the number of theses defended by students of the programme who had several directors and the total number of defended theses in the programme (IPD14)	2022/2023	100
Percentage of examination board members coming from an foreign institution Ratio between the number of examination board members of thesis linked to the programme coming from an foreign institution and the total umber of examination board members of thesis linked to the programme (IPD17)	2022/2023	25
Total number of defended thesis Total number of defended thesis linked to the programme (IPD18.1)	2022/2023	4
Percentage of defended thesis written by full-time students Ratio between the total number of defended thesis written by students under full time status and the total number of defended theses in the programme (IPD18.2.1)	2022/2023	100
Percentage of defended thesis written by partial-time students Ratio between the total number of defended thesis written by students under partial time status and the total number of defended theses in the programme (IPD18.2.2)	2022/2023	0
Percentage of defended thesis written by students under mixed status Ratio between the total number of defended thesis written by students under mixed status and the total number of defended theses in the programme (IPD18.2.3)	2022/2023	0
Total number of tesis written in Galician Total number of defended thesis linked to the programme written in Galician (IPD18.3.1)	2022/2023	0
Total number of tesis written in Spanish Total number of defended thesis linked to the programme written in Spanish (IPD18.3.2)	2022/2023	1
Total number of tesis written in other languages Total number of defended thesis linked to the programme written in other languages (IPD18.3.3)	2022/2023	3
Average duration of studies of full-time students Average duration of studies for students under full time status who defended a thesis (in days) (IPD18.4.1)	2022/2023	1,755
Average duration of studies of partial-time students Average duration of studies for students under half time status who defended a thesis (in days) (IPD18.4.2)	2022/2023	n/a
Average duration of studies of students under mixed time status Average duration of studies for students under mixed time status who defended a thesis (in days) (IPD18.4.3)	2022/2023	n/a
Success rate. Percentage of students who defended their theses without asking for an extension Ratio between the number of doctoral students who defended their theses without asking for an extension and the total number of defended thesis linked to the programme (IPD18.5.1)	2022/2023	0
Success rate. Percentage of students who defended their theses after asking for the first extension Ratio between the number of doctoral students who defended their theses after asking for the first extension and the total number of defended thesis linked to the programme (IPD18.5.2)	2022/2023	50
Success rate. Percentage of students who defended their theses after asking for the second extension Ratio between the number of doctoral students who defended their theses after asking for the second extension and the total number of defended thesis linked to the programme (IPD18.5.3)	2022/2023	50
Percentage of "cum laude" theses Ratio between the number of defended theses linked to the programme with "Cum Laude" qualification and the total number of defended thesis linked to the programme (IPD18.6)	2022/2023	100
Percentage of theses with International Component Ratio between the number of defended theses linked to the programme with International Component and the total number of defended thesis linked to the programme (IPD18.7)	2022/2023	50
Dropout rate Ratio between the number of doctoral students who cause permanent withdrawal from the X course and the total number of doctoral students who could re-enroll in this programme. (IPDx21)	2022/2023	12.77

	Period	Value
Places offered Number of places for new students entering PhD (IPD01)	2021/2022	20
Demand Number of applicants for PhD admission (IPD02)	2021/2022	21
First-time enrollment Number of first-time enrollment students in PhD (IPD03)	2021/2022	16
First-time enrollment by adaptation Number of first-time enrollment students in the program or students coming from other studies in extinction (IPD03.1)	2021/2022	0
Total enrollment Total number of students enrolled (IPD04)	2021/2022	52
First-time enrollment coming from other universities Ratio between the number of first-time enrolled students coming from other universities and the total number of first-time enrolled students in the program (IPD05)	2021/2022	50
Percentage of foreign students Ratio between the number of foreign students enrolled and the total number of students enrolled in the programme (IPD06)	2021/2022	13.46
Percentage of first-time enrolled students who need training complements Ratio between the number of students enrolled who need training complements and the total number of new students enrolled in the programme (IPD07)	2021/2022	0
Percentage of full-time enrollees Ratio between the number of students under full time status and the number of students enrolled in the programme (IPD08.1)	2021/2022	67.31
Percentage of partial-time enrollees Ratio between the number of students under half time status and the number of students enrolled in the programme (IPD08.2)	2021/2022	17.31
Percentage of enrollees under mixed status Ratio between the number of students under mixed status and the number of students enrolled in the programme (IPD08.3)	2021/2022	15.38
Percentage of enrollees who carried out a stay passed by the CAPD (Outgoing) Ratio between the number of students who carried out a stay as visiting researchers passed by the CAPD (outgoing students) and the total number of students enrolled in the programme (IPD09.1)	2021/2022	7.69
Percentage of enrollees who carried out a stay passed by the CAPD at UDC (Incoming) Number of students who carried out a stay as visiting researchers passed by the CAPD (incoming students) (IPD09.2)	2021/2022	n/a
Percentage of enrollees with a grant or pre-doctoral contract Ratio between the number of students with a grant or pre-doctoral contract and the number of students enrolled in the programme (IPD11)	2021/2022	30.77
Percentage of theses defended by students who had several directors Ratio between the number of theses defended by students of the programme who had several directors and the total number of defended theses in the programme (IPD14)	2021/2022	100
Percentage of examination board members coming from an foreign institution Ratio between the number of examination board members of thesis linked to the programme coming from an foreign institution and the total umber of examination board members of thesis linked to the programme (IPD17)	2021/2022	8.33
Total number of defended thesis Total number of defended thesis linked to the programme (IPD18.1)	2021/2022	4
Percentage of defended thesis written by full-time students Ratio between the total number of defended thesis written by students under full time status and the total number of defended theses in the programme (IPD18.2.1)	2021/2022	50
Percentage of defended thesis written by partial-time students Ratio between the total number of defended thesis written by students under partial time status and the total number of defended theses in the programme (IPD18.2.2)	2021/2022	0
Percentage of defended thesis written by students under mixed status Ratio between the total number of defended thesis written by students under mixed status and the total number of defended theses in the programme (IPD18.2.3)	2021/2022	50
Total number of tesis written in Galician Total number of defended thesis linked to the programme written in Galician (IPD18.3.1)	2021/2022	0
Total number of tesis written in Spanish Total number of defended thesis linked to the programme written in Spanish (IPD18.3.2)	2021/2022	2
Total number of tesis written in other languages Total number of defended thesis linked to the programme written in other languages (IPD18.3.3)	2021/2022	2
Average duration of studies of full-time students Average duration of studies for students under full time status who defended a thesis (in days) (IPD18.4.1)	2021/2022	1,636
Average duration of studies of partial-time students Average duration of studies for students under half time status who defended a thesis (in days) (IPD18.4.2)	2021/2022	n/a
Average duration of studies of students under mixed time status Average duration of studies for students under mixed time status who defended a thesis (in days) (IPD18.4.3)	2021/2022	1,936
Success rate. Percentage of students who defended their theses without asking for an extension Ratio between the number of doctoral students who defended their theses without asking for an extension and the total number of defended thesis linked to the programme (IPD18.5.1)	2021/2022	25
Success rate. Percentage of students who defended their theses after asking for the first extension Ratio between the number of doctoral students who defended their theses after asking for the first extension and the total number of defended thesis linked to the programme (IPD18.5.2)	2021/2022	25
Success rate. Percentage of students who defended their theses after asking for the second extension Ratio between the number of doctoral students who defended their theses after asking for the second extension and the total number of defended thesis linked to the programme (IPD18.5.3)	2021/2022	50
Percentage of "cum laude" theses Ratio between the number of defended theses linked to the programme with "Cum Laude" qualification and the total number of defended thesis linked to the programme (IPD18.6)	2021/2022	100
Percentage of theses with International Component Ratio between the number of defended theses linked to the programme with International Component and the total number of defended thesis linked to the programme (IPD18.7)	2021/2022	25
Dropout rate Ratio between the number of doctoral students who cause permanent withdrawal from the X course and the total number of doctoral students who could re-enroll in this programme. (IPDx21)	2021/2022	8.33

	Period	Value
Places offered Number of places for new students entering PhD (IPD01)	2020/2021	20
Demand Number of applicants for PhD admission (IPD02)	2020/2021	23
First-time enrollment Number of first-time enrollment students in PhD (IPD03)	2020/2021	18
First-time enrollment by adaptation Number of first-time enrollment students in the program or students coming from other studies in extinction (IPD03.1)	2020/2021	0
Total enrollment Total number of students enrolled (IPD04)	2020/2021	42
First-time enrollment coming from other universities Ratio between the number of first-time enrolled students coming from other universities and the total number of first-time enrolled students in the program (IPD05)	2020/2021	16.67
Percentage of foreign students Ratio between the number of foreign students enrolled and the total number of students enrolled in the programme (IPD06)	2020/2021	16.67
Percentage of first-time enrolled students who need training complements Ratio between the number of students enrolled who need training complements and the total number of new students enrolled in the programme (IPD07)	2020/2021	0
Percentage of full-time enrollees Ratio between the number of students under full time status and the number of students enrolled in the programme (IPD08.1)	2020/2021	69.05
Percentage of partial-time enrollees Ratio between the number of students under half time status and the number of students enrolled in the programme (IPD08.2)	2020/2021	11.9
Percentage of enrollees under mixed status Ratio between the number of students under mixed status and the number of students enrolled in the programme (IPD08.3)	2020/2021	19.05
Percentage of enrollees who carried out a stay passed by the CAPD (Outgoing) Ratio between the number of students who carried out a stay as visiting researchers passed by the CAPD (outgoing students) and the total number of students enrolled in the programme (IPD09.1)	2020/2021	7.14
Percentage of enrollees who carried out a stay passed by the CAPD at UDC (Incoming) Number of students who carried out a stay as visiting researchers passed by the CAPD (incoming students) (IPD09.2)	2020/2021	n/a
Percentage of enrollees with a grant or pre-doctoral contract Ratio between the number of students with a grant or pre-doctoral contract and the number of students enrolled in the programme (IPD11)	2020/2021	26.19
Percentage of theses defended by students who had several directors Ratio between the number of theses defended by students of the programme who had several directors and the total number of defended theses in the programme (IPD14)	2020/2021	50
Percentage of examination board members coming from an foreign institution Ratio between the number of examination board members of thesis linked to the programme coming from an foreign institution and the total umber of examination board members of thesis linked to the programme (IPD17)	2020/2021	50
Total number of defended thesis Total number of defended thesis linked to the programme (IPD18.1)	2020/2021	2
Percentage of defended thesis written by full-time students Ratio between the total number of defended thesis written by students under full time status and the total number of defended theses in the programme (IPD18.2.1)	2020/2021	100
Percentage of defended thesis written by partial-time students Ratio between the total number of defended thesis written by students under partial time status and the total number of defended theses in the programme (IPD18.2.2)	2020/2021	0
Percentage of defended thesis written by students under mixed status Ratio between the total number of defended thesis written by students under mixed status and the total number of defended theses in the programme (IPD18.2.3)	2020/2021	0
Total number of tesis written in Galician Total number of defended thesis linked to the programme written in Galician (IPD18.3.1)	2020/2021	0
Total number of tesis written in Spanish Total number of defended thesis linked to the programme written in Spanish (IPD18.3.2)	2020/2021	0
Total number of tesis written in other languages Total number of defended thesis linked to the programme written in other languages (IPD18.3.3)	2020/2021	2
Average duration of studies of full-time students Average duration of studies for students under full time status who defended a thesis (in days) (IPD18.4.1)	2020/2021	1,387
Average duration of studies of partial-time students Average duration of studies for students under half time status who defended a thesis (in days) (IPD18.4.2)	2020/2021	n/a
Average duration of studies of students under mixed time status Average duration of studies for students under mixed time status who defended a thesis (in days) (IPD18.4.3)	2020/2021	n/a
Success rate. Percentage of students who defended their theses without asking for an extension Ratio between the number of doctoral students who defended their theses without asking for an extension and the total number of defended thesis linked to the programme (IPD18.5.1)	2020/2021	0
Success rate. Percentage of students who defended their theses after asking for the first extension Ratio between the number of doctoral students who defended their theses after asking for the first extension and the total number of defended thesis linked to the programme (IPD18.5.2)	2020/2021	50
Success rate. Percentage of students who defended their theses after asking for the second extension Ratio between the number of doctoral students who defended their theses after asking for the second extension and the total number of defended thesis linked to the programme (IPD18.5.3)	2020/2021	50
Percentage of "cum laude" theses Ratio between the number of defended theses linked to the programme with "Cum Laude" qualification and the total number of defended thesis linked to the programme (IPD18.6)	2020/2021	100
Percentage of theses with International Component Ratio between the number of defended theses linked to the programme with International Component and the total number of defended thesis linked to the programme (IPD18.7)	2020/2021	50
Dropout rate Ratio between the number of doctoral students who cause permanent withdrawal from the X course and the total number of doctoral students who could re-enroll in this programme. (IPDx21)	2020/2021	7.41

theses

Aprendizaje Automático para la Detección de Anomalías: de la superficie a lo profundo
Novoa Paradela, David

Estimación de la Severidad de la Depresión en Internet: Nuevos Modelos y Recursos
Pérez Vila, Miguel Anxo

Generando explicaciones de sentido común con Answer Set Programming
Muñiz Castro, Brais

Nuevos algoritmos y metodologías para la construcción de colecciones para Recuperación de Información
Otero Freijeiro, David

Aplicación de técnicas de desarrollo automatizado de software en Sistemas de Información Geográfica
Hernández Alvarado, Suilen

Desarrollo de algoritmos eficientes para el ensamblaje de genomas basados en grafos de De Bruijn
Freire Castro, Borja

Detección y caracterización automática de regiones patológicas con fluido en imagen de Tomografía de Coherencia Óptica
Lizancos Vidal, Plácido Francisco

Hacia una detección de anomalías más sostenible: nuevos métodos y aplicaciones prácticas
Novo Meira, Jorge Alexandre

Métodos novedosos de detección de anomalías basados en aprendizaje profundo para el cribado de retinopatía diabética
Sutradhar, Shaon

Captura, representación, consulta y clasificación semántica de trayectorias
Martínez Pérez, Cristina

Modelo de madurez para BizDevOps
Sanjurjo Royo, Eduardo José

Técnicas de Deep Learning para el procesamiento y análisis automático de imagen médica de alta resolución
Suárez Hervella, Álvaro

Perspectivas Diferentes sobre Análisis Sintáctico de Dependencias
Anderson, Mark David

Viabilidad de codificaciones como etiquetado secuencial para el análisis sintáctico de dependencias
Strzyz, Michalina María

Estructuras de datos comprimidas para la representación de trayectorias
Galaktionov Hodovaniuk, Daniil

Estructuras de datos sucintas y autoindexadas para la explotación y representación de objetos móviles
Gómez Brandón, Adrián

Nuevos métodos escalables de aprendizaje máquina: Más allá de la clasificación y la regresión.
Eiras Franco, Carlos

Representación y explotación de secuencias de eventos
Varela Rodeiro, Tirso

Simple pero no simplista: reduciendo la complejidad de métodos de aprendizaje automático
Morán Fernández, Laura

Algoritmos para la medicina del sueño
Fernández Varela, Isaac-Daniel

Buscando robustez en un mundo multilingüe: de pipelines a embeddings
Doval Mosquera, Yerai

Caracterización del Edema Macular Diabético mediante análisis automático de Tomografías de Coherencia Óptica
De Moura Ramos, José Joaquim

Fusión de Información y Ensembles en el Aprendizaje Automático
Seijo Pardo, Borja

Métodos de computación evolutiva para la predicción de la estructura de proteínas y para la modelización computacional del proceso de plegado de proteínas.
Varela Miguéns, Daniel

Modelos de recuperación de información para sistemas de recomendación
Valcarce Silva, Daniel

Estructuras de datos compactas para conjuntos de datos grandes y complejos
Silva Coira, Fernando

Gradación automática de la hiperemia ocular mediante técnicas de procesado de imagen
Sánchez Brea, María Luisa

Línea Producto Software para Sistemas de Información Geográfica en Web
Cortiñas Álvarez, Alejandro

Procesamiento composicional del lenguaje para el análisis del sentimiento multilingüe
Vilares Calvo, David

ANÁLISIS DEL CRECIMIENTO TUMORAL MEDIANTE AUTÓMATAS CELULARES BASADO EN LOS RASGOS CARACTERÍSTICOS DEL CÁNCER
Monteagudo Insua, Ángel

Semantica causal para Programas Lógicos
Fandiño García, Jorge

publications

This is a sample of the scientific production of the PhD students and is intended to guide prospective students interested in this program. Under no circumstances should it be considered a full and exhaustive list of all the scientific production of the students. The information is supplied by the PhD students themselves in a relatively unstructured manner but it has been checked and approved by the academic committee.

Artículos en revistas internacionales

Bao, E., Pérez, A. & Parapar, J. Explainable depression symptom detection in social media. Health Inf Sci Syst12, 47 (2024). https://doi.org/10.1007/s13755-024-00303-9

Otras publicaciones

MetaHate: A Dataset for Unifying Efforts on Hate Speech Detection - Proceedings of the Eighteenth International AAAI Conference on Web and Social Media.

Artículos en revistas internacionales

Paz-Ruza, J., Alonso-Betanzos, A., Guijarro-Berdiñas, B., Cancela, B., & Eiras-Franco, C. (2023). Sustainable Transparency in Recommender Systems: Bayesian Ranking of Images for Explainability. arXiv preprint arXiv:2308.01196

PAZ-RUZA, Jorge, et al. Sustainable Personalisation and Explainability in Dyadic Data Systems. Procedia Computer Science, 2022, vol. 207, p. 1017-1026.

M. Gende, V. Mallén, J. de Moura, B. Cordón, E. Garcia-Martin, C. I. Sánchez, J. Novo, M. Ortega, "Automatic Segmentation of Retinal Layers in Multiple Neurodegenerative Disorder Scenarios", IEEE Journal of Biomedical and Health Informatics, 27 (11), 5483-5494, IEEE , ISSN: 2168-2194, 10.1109/JBHI.2023.3313392 , 2023.

Addressing the data bottleneck in medical deep learning models using a human-in-the-loop machine learning approach Neural Computing and Applications. 2023-11-21 | Journal article DOI: 10.1007/s00521-023-09197-2 Part of ISSN: 0941-0643 Part of ISSN: 1433-3058 CONTRIBUTORS: Eduardo Mosqueira-Rey; Elena Hernández-Pereira; José Bobes-Bascarán; David Alonso-Ríos; Alberto Pérez-Sánchez; Ángel Fernández-Leal; Vicente Moret-Bonillo; Yolanda Vidal-Ínsua; Francisca Vázquez-Rivera

D. I. Morís, J. de Moura, S. Aslani, J. Jacob, J. Novo, M. Ortega. Multi-task localization of the hemidiaphragms and lung segmentation in portable chest X-ray images of COVID-19 patients. Digital Health. 2024;10. doi: 10.1177/20552076231225853

Goyanes, E., de Moura, J., Fernández-Vigo, J. I., Fernández-Vigo, J. A., Novo, J., & Ortega, M. (2024). Automatic simultaneous ciliary muscle segmentation and biomarker extraction in AS-OCT images using deep learning-based approaches. Biomedical Signal Processing and Control90, 105851. DOI: 10.1016/j.bspc.2023.105851

D. I. Morís, J. de Moura, J. Novo, M. Ortega, "Adapted generative latent diffusion models for accurate pathological analysis in chest X-ray images", Medical and Biological Engineering and Computing, 2024. doi: 10.1007/s11517-024-03056-5

CABALAR P, MUÑIZ B. Model Explanation via Support Graphs.Theory and Practice of Logic ProgrammingPublished online 2024:1-14.doi:10.1017/S1471068424000048 >

Morillo-Salas, J. L.Bolón-Canedo, V.Alonso-Betanzos, A.2024The imbalance problem: A comparison of sampling approaches using different parameters and feature selection methods in the context of classificationExpert Systems, e13591. https://doi.org/10.1111/exsy.13591

Mariano Garralda-Barrio, Carlos Eiras-Franco, Verónica Bolón-Canedo, A novel framework for generic Spark workload characterization and similar pattern recognition using machine learning, Journal of Parallel and Distributed Computing, Volume 189, 2024, 104881, ISSN 0743-7315, https://doi.org/10.1016/j.jpdc.2024.104881. (https://www.sciencedirect.com/science/article/pii/S0743731524000455) Abstract: Comprehensive workload characterization plays a pivotal role in comprehending Spark applications, as it enables the analysis of diverse aspects and behaviors. This understanding is indispensable for devising downstream tuning objectives, such as performance improvement. To address this pivotal issue, our work introduces a novel and scalable framework for generic Spark workload characterization, complemented by consistent geometric measurements. The presented approach aims to build robust workload descriptors by profiling only quantitative metrics at the application task-level, in a non-intrusive manner. We expand our framework for downstream workload pattern recognition by incorporating unsupervised machine learning techniques: clustering algorithms and feature selection. These techniques significantly improve the process of grouping similar workloads without relying on predefined labels. We effectively recognize 24 representative Spark workloads from diverse domains, including SQL, machine learning, web search, graph, and micro-benchmarks, available in HiBench. Our framework achieves a high accuracy F-Measure score of up to 90.9% and a Normalized Mutual Information of up to 94.5% in similar workload pattern recognition. These scores significantly outperform the results obtained in a comparative analysis with an established workload characterization approach in the literature. Keywords: Big data; Workload characterization; Apache spark; Pattern recognition; Machine learning

Paz-Ruza, J., Alonso-Betanzos, A., Guijarro-Berdiñas, B., Cancela, B., & Eiras-Franco, C. (2024). Sustainable transparency on recommender systems: Bayesian ranking of images for explainability. Information Fusion, 102497.

Paz-Ruza, J., Alonso-Betanzos, A., Guijarro-Berdiñas, B., Cancela, B., & Eiras-Franco, C. (2024). Beyond RMSE and MAE: Introducing EAUC to unmask hidden bias and unfairness in dyadic regression models. arXiv preprint arXiv:2401.10690

Timiraos, M., Zayas-Gato, F., Michelena, Á., & Arce, E. (2024). Laboratorios virtuales para el aprendizaje a distancia en grados STEAM. Revista de Investigación en Educación22(1), 87-106. DOI: https://doi.org/10.35869/reined.v22i1.5184

Michelena, Á., García Ordás, M. T., Aveleira-Mata, J., Marcos del Blanco, D. Y., Timiraos Díaz, M., Zayas-Gato, F., ... & Luis Calvo-Rolle, J. (2024). Beta Hebbian Learning for intrusion detection in networks with MQTT Protocols for IoT devices. Logic Journal of the IGPL32(2), 352-365.DOI: https://doi.org/10.1093/jigpal/jzae013

Arcano-Bea, P., Timiraos, M., Díaz-Longueira, A., Michelena, Á., Jove, E., & Calvo-Rolle, J. L. (2024). A One-Class-Based Supervision System to Detect Unexpected Events in Wastewater Treatment Plants. Applied Sciences14(12), 5185.DOI: https://doi.org/10.3390/app14125185

Michelena, Á., Zayas-Gato, F., Jove, E., Casteleiro-Roca, J. L., Quintián, H., Fontenla-Romero, Ó., & Luis Calvo-Rolle, J. (2024). Novel adaptive approach for anomaly detection in nonlinear and time-varying industrial systems. Logic Journal of the IGPL, jzae070.DOI: https://doi.org/10.1093/jigpal/jzae070

A. Anido-Alonso and D. Alvarez-Estevez, "Decentralized Data-Privacy Preserving Deep-Learning Approaches for Enhancing Inter-Database Generalization in Automatic Sleep Staging," in IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 11, pp. 5610-5621, Nov. 2023, doi: 10.1109/JBHI.2023.3310869.

Suárez-Marcote, S., Morán-Fernández, L., & Bolón-Canedo, V. (2024). Towards federated feature selection: Logarithmic division for resource-conscious methods. Neurocomputing, 596, 128099. https://doi.org/10.1016/j.neucom.2024.128099

Goyanes, E., de Moura, J., Fernández-Vigo, J.I. et al. 3D Features Fusion for Automated Segmentation of Fluid Regions in CSCR Patients: An OCT-based Photodynamic Therapy Response Analysis. J Digit Imaging. Inform. med. (2024). https://doi.org/10.1007/s10278-024-01190-y

Jorge Paz-Ruza, Alex A. Freitas, Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, Positive-Unlabelled learning for identifying new candidate Dietary Restriction-related genes among ageing-related genes, Computers in Biology and Medicine, Volume 180, 2024, 108999, ISSN 0010-4825, https://doi.org/10.1016/j.compbiomed.2024.108999.

Fernández-Campa-González, Á., Paz-Ruza, J., Alonso-Betanzos, A., & Guijarro-Berdiñas, B. (2024). Positive-Unlabelled Learning for Improving Image-based Recommender System Explainability. arXiv preprint arXiv:2407.06740

Rivas-Villar, D., Hervella, Á.S., Rouco, J. et al. ConKeD: multiview contrastive descriptor learning for keypoint-based retinal image registration. Med Biol Eng Comput (2024). https://doi.org/10.1007/s11517-024-03160-6

M. Gende, L. Castelo, J. de Moura, J. Novo, M. Ortega, "Intra- and inter-expert validation of an automatic segmentation method for fluid regions associated with central serous chorioretinopathy in OCT images", Journal of Imaging Informatics in Medicine, 1-16, Springer, ISSN: 2948-2933, 10.1007/s10278-023-00926-6, 2024.

J. FigueroaD. Rivas-VillarJ. RoucoJ. Novo"Phytoplankton detection and recognition in freshwater digital microscopy images using deep learning object detectors"Heliyon2024

De Castro Celard, D.Cortiñas, A.Luaces, M. R.Pedreira, O.Places, A. S.: "Local features: Enhancing variability modeling in software product lines", en Journal of Systems and Software (to appear), Elsevier, NY (Estados Unidos), 2024.

E. López-Varela, J. de Moura, J. Novo, J. I. Fernández-Vigo, Javier Moreno Morillo, J. García-Feijóo, M. Ortega, "Evolutionary multi-target neural network architectures for flow void analysis in optical coherence tomography angiography", Applied Soft Computing, 153, 111304, 2024

Jager, Wander, Guijarro-Berdiñas, Bertha, Bouman, Loes, Antosz, Patrycja, Alonso Betanzos, Amparo, Salt, Douglas, Polhill, J. Gareth, Rodríguez Arias, Alejandro and Sánchez-Maroño, Noelia (2024) 'Simulating the Role of Norms in Processes of Social Innovation: Three Case Studies' Journal of Artificial Societies and Social Simulation 27 (1) 6 . doi: 10.18564/jasss.5168

Rodríguez-Arias, A., Sánchez-Maroño, N., Guijarro-Berdiñas, B. & Alonso-Betanzos, A., Lema-Blanco, I., Dumitru, A. (2022, September). An Agent-Based Model to Simulate the Public Acceptability of Social Innovations. Expert Systems. Wiley. (Aceptada, pendiente de publicación)

Muñoz-Ortiz, A., Gómez-Rodríguez, C. & Vilares, D. Contrasting Linguistic Patterns in Human and LLM-Generated News Text. Artif Intell Rev57, 265 (2024). https://doi.org/10.1007/s10462-024-10903-2

Capítulo de Libro

Jove, E., Michelena, Á., Timiraos, M., López, V. C., Quintian, H., & Calvo-Rolle, J. L. (2024). Intelligent learning models for renewable energy forecasting. In Intelligent Learning Approaches for Renewable and Sustainable Energy (pp. 105-155). Elsevier.Link: https://www.sciencedirect.com/science/article/abs/pii/B978044315806300005X

Intelligent Learning Approaches for Renewable and Sustainable Energy2024, Pages 105-155

Libro

Jove, E., Zayas-Gato, F., Michelena, Á., & Calvo-Rolle, J. L. (Eds.). (2023). Distributed Computing and Artificial Intelligence, Special Sessions II-Intelligent Systems Applications, 20th International Conference. Springer.DOI: https://doi.org/10.1007/978-3-031-38616-9

Otras publicaciones

@inproceedings{bague2022role, ti@inproceedings{bague2022role, title={The role of feature selection in personalized recommender systems.}, author={Bagu{\'e}-Masan{\'e}s, Roger and Bol{\'o}n-Canedo, Ver{\'o}nica and Remeseiro, Beatriz}, booktitle={ESANN}, year={2022} >tle={The role of feature selection in personalized recommender systems.}, author={Bagu{\'e}-Masan{\'e}s, Roger and Bol{\'o}n-Canedo, Ver{\'o}nica and Remeseiro, Beatriz}, booktitle={ESANN}, year={2022} }

Moret-Bonillo, Vicente, Magaz-Romero, Samuel, Mosqueira-Rey, Eduardo, & Alvarez-Estévez, Diego. (2024). D6.14 Final QRBS software and IDC application (1.0). Zenodo. https://doi.org/10.5281/zenodo.10868936

Artículos en revistas internacionales

Morís, D. I., de Moura, J., Novo, J., & Ortega, M. (2022). Unsupervised contrastive unpaired image generation approach for improving tuberculosis screening using chest X-ray images. In Pattern Recognition Letters (Vol. 164, pp. 60–66). Elsevier BV. https://doi.org/10.1016/j.patrec.2022.10.026

Morís, D. I., Hervella, Á. S., Rouco, J., Novo, J., & Ortega, M. (2023). Context encoder transfer learning approaches for retinal image analysis. In Computers in Biology and Medicine (Vol. 152, p. 106451). Elsevier BV. https://doi.org/10.1016/j.compbiomed.2022.106451

M. Naya-Varela, A. Faina, A. Mallo, R.J. Duro. A study of growth based morphological development in neural network-controlled walkers. Neurocomputing, v. 500, pp. 279-294, 2022

M. Gende, J. de Moura, J. Novo, M. G. Penedo, M. Ortega, "A New Generative Approach for Optical Coherence Tomography Data Scarcity: Unpaired Mutual Conversion between Scanning Presets", Medical & Biological Engineering & Computing, Springer, ISSN: 0140-0118, 10.1007/s11517-022-02742-6, 2023.

P. L. VidalJ. de MouraJ. NovoM. G. PenedoM. Ortega"Image-to-Image Translation with Generative Adversarial Networks via Retinal Masks for Realistic Optical Coherence Tomography Imaging of Diabetic Macular Edema Disorders"Biomedical Signal Processing and Control791040982023

P. L. VidalJ. de MouraJ. NovoM. Ortega"Multivendor fully-automatic uncertainty management approaches for the intuitive representation of DME fluid accumulations in OCT images"Medical & Biological Engineering & Computing1-162023

P. L. VidalJ. de MouraP. AlmuiñaM. FernándezM. OrtegaJ. Novo"Comprehensive fully-automatic multi-depth grading of the clinical types of macular neovascularization in OCTA images"Applied Intelligence2023(pending of publication)

Otero, D., Parapar, J., & Barreiro, Á. (2023). Relevance feedback for building pooled test collections. Journal of Information Science0(0). https://doi.org/10.1177/01655515231171085

D. I. MorísJ. de MouraP. J. MarcosE. Míguez-ReyJ. NovoM. Ortega"Comprehensive Analysis of Clinical Data for COVID-19 Outcome Estimation with Machine Learning Models"Biomedical Signal Processing and Control84104818 2023

D. Rivas-Villar, A. S. Hervella, J. Rouco, J. Novo, "Joint keypoint detection and description network for color fundus image registration", Quantitative Imaging in Medicine and Surgery, 13, No. 7, 4540-4562, 2023.

D. Rivas-Villar, A. R. Motschi, M. Pircher, C. K. Hitzenberger, M. Schranz, P. K. Roberts, U. Schmidt-Erfurth, H. Bogunović, "Automated Inter-Device 3D OCT Image Registration using Deep Learning and Retinal Layer Segmentation", Biomedical Optics Express, 14, 3726--3747, 2023

Magaz-Romero, S., Mosqueira-Rey, E., Alvarez-Estevez, D., Moret-Bonillo, V. (2023). Quantum Factory Method: A Software Engineering Approach to Deal with Incompatibilities in Quantum Libraries. In: Mikyška, J., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2023. ICCS 2023. Lecture Notes in Computer Science, vol 10477. Springer, Cham. https://doi.org/10.1007/978-3-031-36030-5_6

M. Gende, J. de Moura, J. I. Fernández-Vigo, J. M. Martinez-de-la-Casa, J. García-Feijóo, J. Novo, M. Ortega, "Robust Multi-view Approaches for Retinal Layer Segmentation in Glaucoma Patients via Transfer Learning", Quantitative Imaging in Medicine and Surgery, 13 (5), 2846-2859, 2023.

D.Novoa-Paradela,O.Fontenla-Romero,and B.Guijarro-Berdiñas,“Fast deep autoencoder for federated learning,” Pattern Recognitionp.109805, 2023.[Online]. Available: https://www.sciencedirect.com/science/article/pii/S0031320323005034https://doi.org/10.1016/j.patcog.2023.109805

Gutiérrez Asorey, P.Brisaboa, N. R.Varela Rodeiro, T.: "SIGTRANS: Geographical Information System for the analysis and management of public TRANSport", en Kalpa Publications in Computing, 14, EasyChair Ltd, Stockport (Reino Unido), 2023, pp. 7-9.

Lamas Sardiña, V.Cortiñas, A.Luaces, M. R.Pedreira, O.: "Component for the visualization of a spatio-temporal data warehouse in a Geographic Information System", en Kalpa Publications in Computing, 14, EasyChair Ltd, Stockport (Reino Unido), 2023, pp. 139-141.

Pedreira, O.; Ramos Vidal, D.; Cortiñas, A.; Luaces, M. R.; Places, A. S.: "Development of Digital Libraries with Software Product Line Engineering", en Journal of Web Engineering, 20(7), River Publishers, Gistrup (Dinamarca), 2021, pp. 2017-2058.

Ramos Vidal, D.; Cortiñas, A.; Luaces, M. R.; Pedreira, O.; Places, A. S.: "Reducing complexity and cost of Digital Libraries development through Software Product Line Engineering", en Kalpa Publications in Computing, 14, EasyChair Ltd, Stockport (Reino Unido), 2023, pp. 133-135.

J. I. Fernández-VigoJavier Moreno MorilloE. López-VarelaJ. NovoM. OrtegaB. Burgos-BlascoLorenzo López GuajardoJuan Donate López"Repeatability of choriocapillaris flow voids by optical coherence tomography angiography in central serous chorioretinopathy"Plos One17e0279243 2022

E. López-VarelaJ. de MouraJ. NovoJ. I. Fernández-VigoJavier Moreno MorilloM. Ortega"Fully automatic segmentation and monitoring of choriocapillaris flow voids in OCTA images"Computerized Medical Imaging and Graphics104102172 2023

E. López-VarelaN. BarreiraN. OlivierR. ArroyoM. G. Penedo"Generation of synthetic intermediate slices in 3D OCT cubes for improving pathology detection and monitoring"Computers in Biology and Medicine 2023

Mosqueira-Rey, E., Hernández-Pereira, E., Alonso-Ríos, D., Bobes-Bascarán, J., & Fernández-Leal, Á. (2023). Human-in-the-loop machine learning: A state of the art. Artificial Intelligence Review56(4), 3005-3054.

Zayas-Gato, F., Michelena, Á., Jove, E. et al. A distributed topology for identifying anomalies in an industrial environment. Neural Comput & Applic34, 20463–20476 (2022). https://doi.org/10.1007/s00521-022-07106-7

Arce, E., Zayas-Gato, F., Suárez-García, A., Michelena, Álvaro, Jove, E., Casteleiro-Roca, J.-L., Quintián, H. ., & Calvo-Rolle, J. L. . (2022). Experiencia blended learning apoyada en un laboratorio virtual para educación de materias STEM. Bordón. Revista De Pedagogía74(4), 125–143. https://doi.org/10.13042/Bordon.2022.95592

Michelena, Á.; López, V.C.; López, F.L.; Arce, E.; Mendoza García, J.; Suárez-García, A.; García Espinosa, G.; Calvo-Rolle, J.-L.; Quintián, H. A Fault-Detection System Approach for the Optimization of Warship Equipment Replacement Parts Based on Operation Parameters. Sensors202323, 3389. https://doi.org/10.3390/s23073389

Michelena, Álvaro, et al. «A Novel Intelligent Approach for man‐in‐the‐middle Attacks Detection over Internet of Things Environments Based on Message Queuing Telemetry Transport». Expert Systems, febrero de 2023. https://doi.org/10.1111/exsy.13263.

Filgueiras, J.L., Varela, D. & Santos, J. Protein structure prediction with energy minimization and deep learning approaches. Nat Comput (2023). https://doi.org/10.1007/s11047-023-09943-4

Blanco-Mallo, E., Morán-Fernández, L., Remeseiro, B., & Bolón-Canedo, V. (2023). Do all roads lead to Rome? Studying distance measures in the context of machine learning. Pattern Recognition141, 109646. (https://doi.org/10.1016/j.patcog.2023.109646

Y. Zhou, M. A. Chia, S. K. Wagner, M. S. Ayhan, D. Williamson, R. Struyven, T. Liu, M. Xu, M. Gende, P. Woodward-Court, Y. Kihara, UK Biobank Eye & Vision Consortium, A. Altmann, A. Y. Lee, E. J. Topol, A. K. Denniston, D. Alexander, P. A. Keane, "A foundation model for diverse and generalizable disease detection from retinal images", Nature, Nature Portfolio, ISSN: 0028-0836, https://doi.org/10.1038/s41586-023-06555-x, 2023.

Filgueiras, J.L., Varela, D., Santos, J. (2022). Energy Minimization vs. Deep Learning Approaches for Protein Structure Prediction. In: Ferrández Vicente, J.M., Álvarez-Sánchez, J.R., de la Paz López, F., Adeli, H. (eds) Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence. IWINAC 2022. Lecture Notes in Computer Science, vol 13259. Springer, Cham. https://doi.org/10.1007/978-3-031-06527-9_11

Paola Carou-Senra, Jun Jie Ong, Brais Muniz Castro, Iria Seoane-Viano, Lucía Rodríguez-Pombo, Pedro Cabalar, Carmen Alvarez-Lorenzo, Abdul W Basit, Gilberto Pérez, Alvaro Goyanes: Inkjet printing has been extensively explored in recent years to produce personalised medicines due to its low cost and versatility, International Journal of Pharmaceutics: X, Volume 5,2023,100181,ISSN 2590-1567, https://doi.org/10.1016/j.ijpx.2023.100181

En trámite de redacción de un artículo que recoge los resultados de varios workshops realizados a finales del 2022 y principios del 2023, con el título de "Adaptive Portfolio Management based on Complexity Theory and Sociotechnical Design" para enviar a publicar en la revista Journal of the Association for Information System.

Libro

MICHELENA, A., CASTELEIRO-ROCA, J.L., JOVE, E., ZAYAS-GATO, F., QUINTIÁN, H., CALVO-ROLLE, J.L. (2022). Creación de laboratorios virtuales para asignaturas de control con Factory I/O® y Simulink®. A Coruña: Universidade da Coruña, Servizo de Publicacións. ISBN: 978-84-9749-837-1. DOI: https://doi.org/10.17979/spudc.9788497498371

Otras publicaciones

Moret-Bonillo, Vicente, Gomez-Tato, Andres, Magaz-Romero, Samuel, Mosqueira-Rey, Eduardo, & Alvarez-Estevez, Diego. (2022). D6.9: QRBS software specifications. Zenodo. Retrieved from https://doi.org/10.5281/zenodo.7274558

Moret-Bonillo, Vicente, Gomez Tato, Andres, Magaz-Romero, Samuel, Mosqueira-Rey, Eduardo, & Alvarez-Estevez, Diego. (2023). D6.11 Preliminary QRBS software and IDC application specification (1.1). Zenodo. https://doi.org/10.5281/zenodo.8108580

Pérez, A., Fernández-Pichel, M., Parapar, J., & Losada, D. E. (2023). DepreSym: A Depression Symptom Annotated Corpus and the Role of LLMs as Assessors of Psychological Markers. arXiv preprint arXiv:2308.10758

Recensiones

2022. Proceedings of the 31st ACM International Conference on Information & Knowledge Management. Association for Computing Machinery, New York, NY, USA.

2021. Proceedings of the 30th ACM International Conference on Information & Knowledge Management. Association for Computing Machinery, New York, NY, USA.

Artículos en revistas internacionales

Fernández-Barrero, D.; Fontenla-Romero, O.; Lamas-López, F.; Novoa-Paradela, D.; R-Moreno, M.D.; Sanz, D. SOPRENE: Assessment of the Spanish Armada’s Predictive Maintenance Tool for Naval Assets. Appl. Sci.202111, 7322. https://doi.org/10.3390/app11167322

Botana, I.L.-R.; Eiras-Franco, C.; Alonso-Betanzos, A. Regression Tree Based Explanation for Anomaly Detection Algorithm. Proceedings202054, 7. https://doi.org/10.3390/proceedings2020054007

M. GendeJ. de MouraJ. NovoP. CharlónM. Ortega"Automatic Segmentation and Intuitive Visualisation of the Epiretinal Membrane in 3D OCT Images Using Deep Convolutional Approaches"IEEE Access975993 - 76004IEEEISSN: 2169-353610.1109/ACCESS.2021.3082638 2021

J. MoranoA. S. HervellaJ. NovoJ. Rouco"Simultaneous segmentation and classification of the retinal arteries and veins from color fundus images"Artificial Intelligence in Medicine118 2021. DOI: 10.1016/j.artmed.2021.102116

Morís, D. I., de Moura Ramos, J. J., Buján, J. N., & Hortas, M. O. (2021). Data augmentation approaches using cycle-consistent adversarial networks for improving COVID-19 screening in portable chest X-ray images. Expert Systems with Applications185, 115681.

D. Rivas-Villar, Álvaro S. Hervella, J. Rouco, J. Novo, Color fundusimage registration using a learning-based domain-specific landmark detection methodology, Computers in Biology and Medicine 140 (2022) 105101. doi:https://doi.org/10.1016/j.compbiomed.2021.105101.

@article{darriba2021procesamiento, title={Procesamiento de Expresiones Multipalabra en gallego mediante Aprendizaje Profundo}, author={Darriba, V{\'\i}ctor and Doval, Yerai and Kuriyozov, Elmurod}, journal={Procesamiento del Lenguaje Natural}, volume={67}, pages={45--57}, year={2021} >

M. GendeJ. de MouraJ. NovoM. Ortega"End-to-End Multi-Task Learning Approaches for the Joint Epiretinal Membrane Segmentation and Screening in OCT Images"Computerized Medical Imaging and Graphics98102068ElsevierISSN: 0895-611110.1016/j.compmedimag.2022.102068 2022

@article{kuriyozov2022construction, author={Kuriyozov, Elmurod and Matlatipov, Sanatbek and Alonso, Miguel A. and G{\'o}mez-Rodr{\'i}guez, Carlos}, editor={Vetulani, Zygmunt and Paroubek, Patrick and Kubis, Marek}, title={Construction and Evaluation of Sentiment Datasets for Low-Resource Languages: The Case of {U}zbek}, journal={Lecture Notes in Artificial Intelligence}, booktitle={Human Language Technology. Challenges for Computer Science and Linguistics}, year={2022}, publisher={Springer International Publishing}, address={Cham}, volume={13212}, pages={232--243}, isbn={978-3-031-05328-3}, issn={0302-9743}, doi={10.1007/978-3-031-05328-3\_15},

Jun Jie Ong, Brais Muñiz Castro, Simon Gaisford, Pedro Cabalar, Abdul W Basit, Gilberto Pérez, Alvaro Goyanes,Accelerating 3D printing of pharmaceutical products using machine learning,International Journal of Pharmaceutics: X,Volume 4 ,December 2022,100120,ISSN 2590-1567,https://doi.org/10.1016/j.ijpx.2022.100120.

J. de MouraP. L. VidalJ. NovoJ. RoucoM. G. PenedoM. Ortega"Feature definition and comprehensive analysis on the robust identification of intraretinal cystoid regions using Optical Coherence Tomography images"Pattern Analysis and Applications1-15 2022

E. López-VarelaP. L. VidalN. OlivierJ. NovoM. Ortega"Fully-automatic 3D intuitive visualization of Age-related Macular degeneration fluid accumulations in OCT cubes"Journal of Digital Imaging 2022

J. -A. Hitar-Garcia, L. Moran-Fernandez and V. Bolon-Canedo, "Machine Learning Methods for Predicting League of Legends Game Outcome," in IEEE Transactions on Games, doi: 10.1109/TG.2022.3153086.

Fariña, A.Gutiérrez Asorey, P.Ladra, S.Penabad, M. R.Varela Rodeiro, T.: "A Compact Representation for Indoor Trajectories", en IEEE Pervasive Computing, 21(1), IEEE Computer SOC, California (Estados Unidos), 2022, pp. 57-64.

Brisaboa, N. R.Gutiérrez Asorey, P.Luaces, M. R.Varela Rodeiro, T.: "Succinct Data Structures in the Realm of GIS", en Engineering Proceedings, 7(29), MDPI, Basel (Suiza), 2021.

David Otero, Patricia Martin-Rodilla, and Javier Parapar. 2021. Building Cultural Heritage Reference Collections from Social Media through Pooling Strategies: The Case of 2020’s Tensions Over Race and Heritage. J. Comput. Cult. Herit. 15, 1, Article 9 (February 2022), 13 pages. https://doi.org/10.1145/3477604

Pérez, A., Parapar, J., & Barreiro, Á. (2022). Automatic depression score estimation with word embedding models. Artificial Intelligence in Medicine, 102380.

D. Novoa-Paradela,O. Fontenla-Romero, B. Guijarro-Berdiñas, A one-class classification method based on expanded non-convex hulls, Information Fusion 89 (2023) 1–15. doi:https://doi.org/10.1016/j.inffus.2022.07.023

Eduardo Mosqueira-Rey, Elena Hernández-Pereira, David Alonso-Ríos, José Bobes-Bascarán & Ángel Fernández-Leal. Human-in-the-loop machine learning: a state of the art. Artif Intell Rev (2022). https://doi.org/10.1007/s10462-022-10246-w

Cristian R. Munteanu; Gutiérrez Asorey, P.; Outros: "Prediction of Anti-Glioblastoma Drug-Decorated Nanoparticle Delivery Systems Using Molecular Descriptors and Machine Learning", en International Journal of Molecular Sciences, 22, MDPI, Basel (Suíza), 2021.

Meira, Jorge, et al. "Anomaly Detection on Natural Language Processing to Improve Predictions on Tourist Preferences." Electronics 11.5 (2022): 779.

Meira, Jorge, et al. "Fast anomaly detection with locality-sensitive hashing and hyperparameter autotuning." Information Sciences 607 (2022): 1245-1264.

J. I. Fernández-VigoJavier Moreno MorilloM. OrtegaE. López-VarelaJ. NovoB. Burgos-BlascoLorenzo López GuajardoJ. García-FeijóoJuan Donate López"Early changes in choriocapillaris flow voids as an efficacy biomarker of photodynamic therapy in central serous chorioretinopathy"Photodiagnosis and Photodynamic Therapy38102862 2022

E. López-VarelaP. L. VidalN. OlivierJ. NovoM. Ortega"Fully-automatic 3D intuitive visualization of Age-related Macular degeneration fluid accumulations in OCT cubes"Journal of Digital Imaging 2022

Freire B, Ladra S, Parama JR, Salmela L. ViQUF: De Novo Viral Quasispecies Reconstruction Using Unitig-Based Flow Networks. IEEE/ACM Trans Comput Biol Bioinform. 2022 Jul 19;PP. doi: 10.1109/TCBB.2022.3190282. Epub ahead of print. PMID: 35853050.

Moret-Bonillo, V., Magaz-Romero, S., & Mosqueira-Rey, E. (2022). Quantum Computing for Dealing with Inaccurate Knowledge Related to the Certainty Factors Model. Mathematics10(2), 189. MDPI AG. Retrieved from http://dx.doi.org/10.3390/math10020189

De Castro Celard, D.Cortiñas, A.Luaces, M. R.Pedreira, O.: "Product configuration of a software product line using a Domain Specific Language", en Kalpa Publications in Computing, 14, EasyChair Ltd, Stockport (Reino Unido), 2023, pp. 50-52.

Capítulo de Libro

Morís, D. I., de Moura, J., Novo, J., & Ortega, M. (2022). Generation of Novel Synthetic Portable Chest X-Ray Images for Automatic COVID-19 Screening. In AI Applications for Disease Diagnosis and Treatment (pp. 248-281). IGI Global.

M. GendeJ. de MouraJ. NovoM. Ortega"Fully Automatic Epiretinal Membrane Segmentation in OCT Scans Using Convolutional Networks"AI Applications for Disease Diagnosis and Treatment88-121 2022

Otras publicaciones

D. Novoa-Paradela, O. Romero-Fontenla, B. Guijarro-Berdiñas, Fast deep autoencoder for federated learning (2022). doi:10.48550/ARXIV.2206.05136.

Using Machine Learning to Predict the Users Ratings on TripAdvisor Based on Their Reviews

Moret-Bonillo, Vicente, Mosqueira-Rey, Eduardo, & Magaz-Romero, Samuel. (2021). D6.5 Quantum Rule-Based System (QRBS) Requirement Analysis. Zenodo. Retrieved from https://doi.org/10.5281/zenodo.5949157

Artículos en revistas internacionales

Morillo-Salas, J.L., Bolón-Canedo, V. & Alonso-Betanzos, A. Dealing with heterogeneity in the context of distributed feature selection for classification. Knowl Inf Syst (2020). https://doi.org/10.1007/s10115-020-01526-4

Process Reference Model for BizDevOpshttps://ieeexplore.ieee.org/abstract/document/9141123/metrics#metricsElectronic ISBN:978-989-54659-0-3DOI: 10.23919/CISTI49556.2020.9141123

Measuring the Maturity of BizDevOpshttps://link.springer.com/chapter/10.1007/978-3-030-58793-2_16DOI: https://doi.org/10.1007/978-3-030-58793-2_16Online ISBN: 978-3-030-58793-2

P. L. Vidal, J. de Moura, J. Novo, M. Ortega, "Multi-stage transfer learning for lung segmentation using portable X-ray devices for patients with COVID-19", Expert Systems with Applications , 173, 114677, 2021.

J. de Moura, L. Ramos, P. L. Vidal, M. Cruz, L. Abeilairas, E. Castro, J. Novo, M. Ortega, "Deep convolutional approaches for the analysis of Covid-19 using chest X-Ray images from portable devices", IEEE Access, 8, 195594-195607, 2020.

P. L. Vidal, J. de Moura, M. Díaz, J. Novo, M. Ortega, "Diabetic Macular Edema characterization and visualization using Optical Coherence Tomography Images", Applied Sciences, 10, 1-23, 2020.

Alvarado, S. H., Cortiñas, A., Luaces, M. R., Pedreira, O., & Places, A. S. (2021). Multilevel modeling of geographic information systems based on international standards. Software and Systems Modeling, 1-44.

Memory-Efficient Assembly using Flye, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10.1109/TCBB.2021.3108843

Moe Elbadawi, Brais Muñiz Castro, Francesca K.H. Gavins, Jun Jie Ong, Simon Gaisford, Gilberto Pérez, Abdul W. Basit, Pedro Cabalar, Alvaro Goyanes, M3DISEEN: A novel machine learning approach for predicting the 3D printability of medicines, International Journal of Pharmaceutics, Volume 590, 2020, 119837, ISSN 0378-5173, https://doi.org/10.1016/j.ijpharm.2020.119837.

Brais Muñiz Castro, Moe Elbadawi, Jun Jie Ong, Thomas Pollard, Zhe Song, Simon Gaisford, Gilberto Pérez, Abdul W. Basit, Pedro Cabalar, Alvaro Goyanes, Machine learning predicts 3D printing performance of over 900 drug delivery systems, Journal of Controlled Release, Volume 337, 2021, Pages 530-545, ISSN 0168-3659, https://doi.org/10.1016/j.jconrel.2021.07.046.

A. S. Hervella. J. Rouco, J. Novo, M. Ortega. Self-supervised multimodal reconstruction pre-training for retinal computer-aided diagnosis. Expert Systems with Applications, 185 (2021).https://doi.org/10.1016/j.eswa.2021.115598

J. Morano, A. S. Hervella, J. Novo, J. Rouco, Simultaneous segmentation and classification of the retinal arteries and veins from color fundus images, Artificial Intelligence in Medicine, 118 (2021).https://doi.org/10.1016/j.artmed.2021.102116

Capítulo de Libro

A. S. Hervella, J. Rouco, J. Novo, M. Ortega, Chapter 15 - Multimodal reconstruction of retinal images over unpaired datasets using cyclical generative adversarial networks, Generative Adversarial Networks for Image-to-Image Translation, Academic Press, 2021.https://doi.org/10.1016/B978-0-12-823519-5.00014-2

Otras publicaciones

De Berardinis, Jacopo, et al. "At Your Service: Coffee Beans Recommendation From a Robot Assistant." Proceedings of the 8th International Conference on Human-Agent Interaction. 2020.

Martinho, Diogo, et al. "A Hybrid Model to Classify Patients with Chronic Obstructive Respiratory Diseases." Journal of Medical Systems 45.3 (2021): 1-11.

Meira et al. "Predictive Maintenance Through Data-driven Approaches", DISRUPTIVE 2020

Meira et al. "Route Optimization For A Beer Deliver Decision Support System", DISRUPTIVE 2021.

Meira et al. "A Machine learning based framework for PdM", DISRUPTIVE 2021

Carneiro, João et al. “Using Machine Learning to Predict the Users Ratings on TripAdvisor Based on their Reviews”, PAAMS 2021

Artículos en revistas internacionales

Díaz, M.; Díez-Sotelo, M.; Gómez-Ulla, F.; Novo, J.; Penedo, M.F.G.; Ortega, M. Automatic Visual Acuity Estimation by Means of Computational Vascularity Biomarkers Using Oct Angiographies. Sensors201919, 4732.

Vázquez, A., López-López, N., Houenou, J. et al. Automatic group-wise whole-brain short association fiber bundle labeling based on clustering and cortical surface information. BioMed Eng OnLine19, 42 (2020). https://doi.org/10.1186/s12938-020-00786-z

Vázquez, A., López-López, N., Sánchez, A., Houenou, J., Poupon, C., Mangin, J. F., Hernández, C. & Guevara, P. (2020). FFClust: Fast fiber clustering for large tractography datasets for a detailed study of brain connectivity. NeuroImage, 117070. https://doi.org/10.1016/j.neuroimage.2020.117070

López-López, N., Vázquez, A., Houenou, J., Poupon, C., Mangin, J. F., Ladra, S., & Guevara, P. (2020). From coarse to fine-grained parcellation of the cortical surface using a fiber-bundle atlas. Frontiers in Neuroinformatics, 14, 32. (To appear)https://www.frontiersin.org/articles/10.3389/fninf.2020.00032/abstract

Meira, Jorge, et al. "Performance evaluation of unsupervised techniques in cyber-attack anomaly detection." Journal of Ambient Intelligence and Humanized Computing (2019): 1-13.

Díaz M, Novo J, Cutrín P, Gómez-Ulla F, Penedo MG, et al. (2019) Automatic segmentation of the foveal avascular zone in ophthalmological OCT-A images. PLOS ONE 14(2): e0212364. https://doi.org/10.1371/journal.pone.0212364

Díez-Sotelo, M., Díaz, M., Abraldes, M., Gómez-Ulla, F., G Penedo, M., & Ortega, M. (2019). A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography. Journal of Clinical Medicine8(10), 1515.

E. J. Carmona, M. Díaz, J. Novo and M. Ortega, "Modeling, Localization, and Segmentation of the Foveal Avascular Zone on Retinal OCT-Angiography Images," in IEEE Access, vol. 8, pp. 152223-152238, 2020, doi: 10.1109/ACCESS.2020.3017440.

P. L. VidalJ. de MouraJ. NovoM. G. PenedoM. Ortega"Intraretinal fluid identification via enhanced maps using Optical Coherence Tomography images"Biomedical Optics Express9(10)4730-47542018

J. de MouraP. L. VidalJ. NovoJ. RoucoM. G. PenedoM. Ortega"Intraretinal fluid pattern characterization in Optical Coherence Tomography images"Sensors20(7), 20041-232020

Alvarado, S. H. (2019). Design of Mutation Operators for Testing Geographic Information Systems. In Multidisciplinary Digital Publishing Institute Proceedings (Vol. 21, No. 1, p. 43).

Alvarado, S. H., Cortinas, A., Luaces, M. R., Pedreira, O., & Places, A. S. (2019, September). Applying Multilevel Modeling to the Development of Geographic Information Systems. In 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C) (pp. 128-133). IEEE.

Alvarado, S. H., Cortiñas, A., Luaces, M. R., Pedreira, O., & Places, Á. S. (2019). A Domain Specific Language for Web-based GIS. In WEBIST (pp. 462-469).

Alvarado, S. H., Cortiñas, A., Luaces, M. R., Pedreira, O., & Places, Á. S. (2020). Developing Web-based Geographic Information Systems with a DSL: Proposal and Case Study. Journal of Web Engineering, 167-194.

Parallel Feature Selection for distributed-memory cluster, Information Science, september 2019, Doi 10.1016/j.ins.2019.01.050Inference of viral quasispecies with a paired de Bruijn graph, Bioinformatics 2020, pendiente de publicar pero ya aceptado

A. S. Hervella, J. Rouco, J. Novo, M. G. Penedo, M. Ortega. Deep multi-instance heatmap regression for the detection of retinal vessel crossings and bifurcations in eye fundus images. Computer Methods and Programs in Biomedicine, 186 (2020)

A. S. Hervella, J. Rouco, J. Novo, M. Ortega. Self-supervised multimodal reconstruction of retinal images over paired datasets. Expert Systems with Applications, 161 (2020)

A. S. Hervella, J. Rouco, J. Novo, M. Ortega. Learning the retinal anatomy from scarce annotated data using self-supervised multimodal reconstruction. Applied Soft Computing, (2020)

Inference of viral quasispecies with a paired de Bruijn graph; Borja Freire, Susana Ladra, José Ramón Parama, Leena Salmela, 10.1093/bioinformatics/btaa782

Artículos en revistas nacionales

Alvarado12, S. H., de Guzmán, I. G. R., Luaces, M. R., Pedreira, O., Places, Á. S., & Polo, M. Definición de Operadores de Mutación para Sistemas de Información Geográfica.

Capítulo de Libro

P. L. VidalJ. de MouraJ. NovoM. G. PenedoM. Ortega"Intraretinal Fluid Map Generation in Optical Coherence Tomography Images"Diabetes and Retinopathy - Computer-Assisted Diagnosis219-432020

Notas

P. L. VidalJ. de MouraJ. NovoM. G. PenedoM. Ortega"Intuitive and coherent intraretinal cystoid map representation in Optical Coherence Tomography images"Lecture Notes in Computer Science: Computer Aided Systems Theory, Revised Selected Papers, EUROCAST 201912014270-278Las Palmas de Gran Canaria, Spain2020

Otras publicaciones

I. Huerta, A. Vázquez, N. López-López, J. Houenou, C. Poupon, J.-F. Mangin, P. Guevara, C. Hernández. Inter-Subject Clustering of Brain Fibers from Whole-Brain Tractography. XII Congreso Anual de Ingeniería Biomédica (CAIB XII), Concepción, Chile, 2019.

N. López-López, A. Vázquez, C. Poupon, J. Mangin and P. Guevara, "Cortical surface parcellation based on intra-subject white matter fiber clustering," 2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON), Valparaiso, Chile, 2019, pp. 1-6.

Nieves R. Brisaboa, Antonio Fariña, Adrián Gómez-Brandón, Gonzalo Navarro, Tirso V. Rodeiro: Dv2v: A Dynamic Variable-to-Variable Compressor. DCC 2019:83-92.

Gómez-Brandón, A.: Bitvectors with runs and the succes- sor/predecessor problem. In Proceedings of the 2020 Data Compression Conference (DCC 2020) IEEE Computer Society, Snowbird, Utah (United States), 2020, pp. 133-142.

N. López-López, A. Vázquez, C. Poupon, J.-F. Mangin, S. Ladra, and P. Guevara. GeoSP: A parallel method for a cortical surface parcellation based on geodesic distance. In 2020 42th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2020.

I. Huerta, A. Vázquez, N. López-López, J. Houenou, C. Poupon, J.-F. Mangin, P. Guevara, and C. Hernández. Inter-subject clustering of brain fibers from whole-brain tractography. In 2020 42th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2020.

P. L. VidalJ. de MouraJ. NovoJ. RoucoM. Ortega"Intraretinal Fluid Pattern Characterization"Scholarly Community Encyclopedia1-52020

Vilares, D. and Strzyz, M. and Søgaard, A. and Gómez-Rodríguez, C. Parsing as Pretraining. In AAAI 2020

Artículos en revistas internacionales

Daniel Valcarce, Javier Parapar, Álvaro Barreiro. Document-based and Term-based Linear Methods for Pseudo-Relevance Feedback. Applied Computing Review, vol. 18(4), pp. 5-17, 2018.

Daniel Valcarce, Igo Brilhante, Jose Antonio Macedo, Franco Maria Nardini, Raffaele Perego, Chiara Renso. Item-driven group formation. Online Social Networks and Media, vol. 8, pp. 17-31, 2018. DOI 10.1016/j.osnem.2018.10.002

González-López, A., de Moura, J., Novo, J., Ortega, M., & Penedo, M. G. (2019). Robust segmentation of retinal layers in optical coherence tomography images based on a multistage active contour model. Heliyon5(2), e01271.

de Moura, J., Novo, J., Rouco, J., Charlón, P., & Ortega, M. (2019). Artery/Vein Vessel Tree Identification in Near-Infrared Reflectance Retinographies. Journal of digital imaging, 1-16.

Brisaboa, N. R.; Gomez Brandon, A.; Navarro, G.; Paramá, J. R.: "GraCT: A Grammar-based Compressed Index for Trajectory Data", en Information Sciences, 483, Elsevier, New York (Estados Unidos), 2019, pp. 106-135.

Large scale anomaly detection in mixed numerical and categorical input spaces - Information Sciences - https://doi.org/10.1016/j.ins.2019.03.013

A. Fernández, M. Ortega, J. de Moura, J. Novo, M. G. Penedo, Automatic evaluation of eye gestural reactions to sound in video sequences, Engineering Applications of Artificial Intelligence, 85, 164-174, Elsevier, ISSN: 0952-1976, 10.1016/j.engappai.2019.06.009, 2019.

Montero-Manso, P., Morán-Fernández, L., Bolón-Canedo, V., Vilar, J. A., & Alonso-Betanzos, A. (2018). Distributed classification based on distances between probability distributions in feature space. Information Sciences

S. BaamondeJ. de MouraJ. NovoP. CharlónM. Ortega"Automatic identification and characterization of the Epiretinal Membrane in OCT images"Biomedical Optics Express 10 (8)4018-4033OSA PublishingISSN: 2156-708510.1364/BOE.10.004018 2019

Eiras-Franco, C., Guijarro-Berdiñas, B., Alonso-Betanzos, A., Bahamonde, A. A scalable decision-tree-based method to explain interactions in dyadic data. Decision Support Systems. (2019) https://doi.org/10.1016/j.dss.2019.113141

Large-scale validation of an automatic EEG arousal detection algorithm using different heterogeneous databasesD Alvarez-Estevez, I Fernández-VarelaSleep medicine 57, 6-14

Seijo-Pardo, B., Bolón-Canedo, V., & Alonso-Betanzos, A. (2019). On developing an automatic threshold applied to feature selection ensembles. Information Fusion45, 227-245.

Seijo-Pardo, B., Alonso-Betanzos, A., Bennett, K. P., Bolón-Canedo, V., Josse, J., Saeed, M., & Guyon, I. (2019). Biases in feature selection with missing data. Neurocomputing342, 97-112.

Capítulo de Libro

J. de MouraJ. NovoJ. RoucoN. BarreiraM. G. PenedoM. Ortega"Retinal Vasculature Identification and Characterization Using OCT Imaging"OCT - Applications in Ophthalmology23-40InTechOpenISBN: 978-953-51-6693-1 2018

J. de Moura, J. Novo, M. Ortega, N. Barreira, P. Charlón, "Automatic retinal vascularity identification and artery/vein classification using near-infrared reflectance retinographies", Computer Vision, Imaging and Computer Graphics - Theory and Applications, 983, 262-278, Springer, ISSN: 1865-0929, ISBN: 978-3-030-12208-9, https://doi.org/10.1007/978-3-030-12209-6 _ 13, 2019.

Alonso-Betanzos, A., Bolón-Canedo, V., Morán-Fernández, L., & Seijo-Pardo, B. (2019). Feature Selection Applied to Microarray Data. In Microarray Bioinformatics (pp. 123-152). Humana, New York, NY.

Alonso-Betanzos, A., Bolón-Canedo, V., Morán-Fernández, L., & Sánchez-Maroño, N. (2019). A Review of Microarray Datasets: Where to Find Them and Specific Characteristics. In Microarray Bioinformatics (pp. 65-85). Humana, New York, NY.

Meira, Jorge, et al. "Comparative Results with Unsupervised Techniques in Cyber Attack Novelty Detection." International Symposium on Ambient Intelligence. Springer, Cham, 2018.

P. L. Vidal, J. de Moura, J. Novo, M. G. Penedo, M. Ortega, "Intraretinal Fluid Map Generation in Optical Coherence Tomography Images", Photo Acoustic and Optical Coherence Tomography (OCT) Imaging: an Application in Ophthalmology, 2019. (pending of publication).

J. de Moura, G. Samagaio, J. Novo, M. Fernández, F. Gómez-Ulla, M. Ortega, "Fully Automated Identification and Clinical Classification of Macular Edema Using Optical Coherence Tomography Images", Photo Acoustic and Optical Coherence Tomography (OCT) Imaging: an Application in Ophthalmology, 2019. (pending of publication).

Otras publicaciones

G. SamagaioJ. de MouraJ. NovoM. Ortega"Automatic Identification and Segmentation of Diffuse Retinal Thickening Macular Edemas Using OCT Imaging"XoveTIC 20182(18)1194MDPIISSN: 2504-390010.3390/proceedings218119427/09/2018-28/09/2018A Coruña September 2018

J. de MouraJ. NovoN. BarreiraM. G. PenedoM. Ortega"Automatic system for the identification and visualization of the retinal vessel tree using OCT imaging"XoveTIC 20182(18)1168ISSN: 2504-390010.3390/proceedings218116827/09/2018-28/09/2018A Coruña September 2018

P. L. VidalJ. de MouraJ. NovoJ. RoucoM. Ortega"Fluid region analysis and identification via Optical Coherence Tomography image samples"XoveTIC 20182(18)1180MDPIISSN: 2504-390010.3390/proceedings218118027/09/2018-28/09/2018A Coruña September 2018

S. BaamondeJ. de MouraJ. NovoN. BarreiraM. Ortega"Automatic Characterization of Epiretinal Membrane in OCT Images with Supervised Training"XoveTIC 20182(18)1161MDPIISSN: 2504-390010.3390/proceedings218116127/09/2018-28/09/2018A Coruña September 2018

Alvarez-Estevez, Diego, and Isaac Fernández-Varela. "Large-scale validation of an automatic EEG arousal detection algorithm using different databases." arXiv preprint arXiv:1809.06216(2018).

A. Vázquez, N. López-López, M. Figueroa, C. Hernández, P. Guevara. Optimización paralela para la segmentación de fascículos de fibras en conjuntos masivos de datos de tractografía. XXVII Congreso de Electrónica-Electricidad (INGELECTRA 2018), Valdivia, Chile, 2018.

A. Vázquez, N. López-López, N. Labra, M. Figueroa, C. Poupon, J.-F. Mangin, C. Hernández, P. Guevara. Parallel Optimization of Fiber Bundle Segmentation for Massive Tractography Datasets. IEEE International Symposium on Biomedical Imaging (ISBI’19), Venecia, Italia, 2019.

Meira, Jorge. "Comparative Results with Unsupervised Techniques in Cyber Attack Novelty Detection." XoveTIC 2018: 98.

Brisaboa, N. R.; Fariña, A.; Gomez Brandon, A.; Navarro, G.; Varela Rodeiro, T.: "Dv2v: A Dynamic Variable-to-Variable Compressor", en Proceedings of the 2019 Data Compression Conference (DCC 2019), IEEE Computer Society, Snowbird, Utah (Estados Unidos), 2019, pp. 83-92.

I. Osorio, D. Bonometti, D. Carrasco, A. Vázquez, N. López-López, C. Poupon, J.-F. Mangin, P. Guevara. FiberVis: a tool for a fast fiber tractography visualization and segmentation. Organization for Human Brain Mapping (OHBM 2019), Rome (Italy), 2019.

P. Guevara, C. Román, A. Vazquez, N. López, F. Silva, I. Osorio, D. Bonometti, M. Guevara, N. Labra, N. Cárdenas, L. González, H. Hernández, J. Houenou, C. Poupon, J.-F. Mangin, M. Figueroa and C. Hernández. Analysis tools for the study of brain connectivity based on diffusion MRI. Health Data Science: Conference and Workshops (Make Health Chile 2019), Santiago (Chile), 2019.

Dealing with the database variability problem in learning from medical data: an ensemble-based approach using convolutional neural networks and a case of study applied to …D Alvarez-Estevez, I Fernández-VarelaarXiv preprint arXiv:1906.06666

A Convolutional Network for Sleep Stages ClassificationI Fernández-Varela, E Hernández-Pereira, D Alvarez-Estevez, ...arXiv preprint arXiv:1902.05748

Uncertainty in Quantum Rule-Based SystemsV Moret-Bonillo, I Fernández-Varela, D Álvarez-EstévezarXiv preprint arXiv:1811.02782

Artículos en revistas internacionales

Eduardo Mosqueira-Rey, David Alonso-Ríos, Vicente Moret-Bonillo, Isaac Fernández-Varela, Diego Álvarez-Estévez, A Systematic Approach to API Usability: Taxonomy-derived Criteria and a Case Study, Information and Software Technology, Available online 28 December 2017, ISSN 0950-5849, https://doi.org/10.1016/j.infsof.2017.12.010.

Daniel Valcarce, Javier Parapar, Álvaro Barreiro. Axiomatic Analysis of Language Modelling of Recommender Systems. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 25(Supplement-2): 113-128 (2017). DOI 10.1142/S0218488517400141

de Moura J, Novo J, Charlón P, Barreira N, Ortega M. Enhanced visualization of the retinal vasculature using depth information in OCT. Medical & biological engineering & computing. 2017 Dec 1;55(12):2209-25.

Samagaio G, Estévez A, de Moura J, Novo J, Fernandez MI, Ortega M. Automatic Macular Edema Identification and Characterization Using OCT Images. Computer Methods and Programs in Biomedicine. 16347-63 2018

Fernández A, Ortega M, de Moura J, Novo J, Penedo MG, Detection of reactions to sound via gaze and global eye motion analysis using camera streaming. Machine Vision and Applications, 2018. https://doi.org/10.1007/s00138-018-0952-9

Yerai Doval and Carlos Gómez-Rodríguez Comparing Neural- and N-gram-based Language Models for Word Segmentation Journal of the Association for Information Science and Technology (JASIST), Fothcoming. ISSN 2330-1635

Yerai Doval, Manuel Vilares, Jesús Vilares, On the performance of phonetic algorithms in microtext normalization Expert Systems with Applications Volume 113, 2018, Pages 213-222, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2018.07.016. (http://www.sciencedirect.com/science/article/pii/S0957417418304305) Keywords: Microtext normalization; Phonetic algorithm; Fuzzy matching; Twitter; Texting

Claude, F.; Galaktionov, D.; Konow, Roberto; Ladra, S.; Pedreira, O.: "Competitive Author Profiling Using Compression-Based Strategies", en International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 25(2), World Scientific, Singapur (Singapur), 2017, pp. 5-20.

Brisaboa, N. R.; Fariña, A.; Galaktionov, D.; Rodríguez, M. Andrea: "A Compact Representation for Trips over Networks built on self-indexes", en Information Systems, 78, Elsevier Ltd., Oxford (Reino Unido), 2018, pp. 1-22.

Daniel Valcarce, Javier Parapar, Álvaro Barreiro. A MapReduce implementation of posterior probability clustering and relevance models for recommendation. Engineering Applications of Artificial Intelligence, vol. 75, pp. 114-124, 2018. DOI 10.1016/j.engappai.2018.08.006

Plácido L. Vidal, Joaquim de Moura, Jorge Novo, Manuel G. Penedo, and Marcos Ortega, "Intraretinal fluid identification via enhanced maps using optical coherence tomography images," Biomed. Opt. Express 9, 4730-4754 (2018)

Daniel Valcarce, Javier Parapar, Álvaro Barreiro. Finding and Analysing Good Neighbourhoods to Improve Collaborative Filtering. Knowledge-Based Systems, vol. 159, pp. 193-202, 2018. DOI 10.1016/j.knosys.2018.06.030

Capítulo de Libro

Moret-Bonillo V., Fernández-Varela I., Hernández-Pereira E., Alvarez-Estévez D., Perlitz V. (2018) On The Automation of Medical Knowledge and Medical Decision Support Systems. In: Holmes D., Jain L. (eds) Advances in Biomedical Informatics. Intelligent Systems Reference Library, vol 137. Springer, Cham

de Moura J, Novo J, Ortega M, Barreira N, Charlón P. Artery/vein Classification of Blood Vessel Tree in Retinal Imaging. InVISIGRAPP (4: VISAPP) 2017 (pp. 371-377).

de Moura J, Novo J, Rouco J, Ortega M. Feature definition, analysis and selection for cystoid region characterization in Optical Coherence Tomography. Procedia Computer Science. 2017 Jan 1;112:1369-77.

de Moura J, Novo J, Rouco J, Penedo MG, Ortega M. Automatic vessel detection by means of brightness profile characterization in OCT images. Procedia Computer Science. 2017 Jan 1;112(C):980-8.

de Moura J, Novo J, Rouco J, Penedo MG, Ortega M. Automatic Detection of Blood Vessels in Retinal OCT Images. InInternational Work-Conference on the Interplay Between Natural and Artificial Computation 2017 Jun 19 (pp. 3-10). Springer, Cham.

Baamonde S, de Moura J, Novo J, Ortega M. Automatic Detection of Epiretinal Membrane in OCT Images by Means of Local Luminosity Patterns. InInternational Work-Conference on Artificial Neural Networks 2017 Jun 14 (pp. 222-235). Springer, Cham.

Baamonde S, de Moura J, Novo J, Rouco J, Ortega M. Feature Definition and Selection for Epiretinal Membrane Characterization in Optical Coherence Tomography Images. InInternational Conference on Image Analysis and Processing 2017 Sep 11 (pp. 456-466). Springer, Cham.

Samagaio G, de Moura J, Novo J, Ortega M. Optical Coherence Tomography Denoising by Means of a Fourier Butterworth Filter-Based Approach. InInternational Conference on Image Analysis and Processing 2017 Sep 11 (pp. 422-432). Springer, Cham.

de Moura J, Novo J, Ortega M, Barreira N, Penedo MG. Interactive Three-Dimensional Visualization System of the Vascular Structure in OCT Retinal Images. InInternational Conference on Computer Aided Systems Theory 2017 Feb 19 (pp. 306-313). Springer, Cham.

de Moura J, Novo J, Rouco J, Penedo MG, Ortega M. Automatic Identification of Intraretinal Cystoid Regions in Optical Coherence Tomography. InConference on Artificial Intelligence in Medicine in Europe 2017 Jun 21 (pp. 305-315). Springer, Cham.

Samagaio G, Estévez A, de Moura J, Novo J, Ortega M, Fernández M. Automatic Identification of Macular Edema in Optical Coherence Tomography Images. VISIGRAPP (4: VISIGRAPP) 2018: 533-540

de Moura, J., Novo, J., Penas, S., Ortega, M., Silva, J., & Mendonça, A. M. (2018). Automatic Characterization of the Serous Retinal Detachment Associated with the Subretinal Fluid Presence in Optical Coherence Tomography Images. Procedia Computer Science126, 244-253.

Samagaio, G., de Moura, J., Novo, J., & Ortega, M. (2018). Automatic Segmentation of Diffuse Retinal Thickening Edemas Using Optical Coherence Tomography Images. Procedia Computer Science126, 472-481.

Otras publicaciones

Brisaboa, N. R.de Bernardo, GuillermoNavarro, G.Varela Rodeiro, T.Seco, D.: "Compact Representations of Event Sequences", en Proceedings of the 2018 Data Compression Conference (DCC 2018), IEEE Computer Society, Snowbird, Utah (Estados Unidos), 2018, pp. 239-248.2375-0359/18/$31.00 ©2018 IEEE DOI 10.1109/DCC.2018.00032

Cortiñas A., Luaces M.R., Rodeiro T.V. (2018) A Case Study on Visualizing Large Spatial Datasets in a Web-Based Map Viewer. In: Mikkonen T., Klamma R., Hernández J. (eds) Web Engineering. ICWE 2018. Lecture Notes in Computer Science, vol 10845. Springer, Cham

Cortiñas A., Luaces M.R., Rodeiro T.V. (2018) Storing and Clustering Large Spatial Datasets Using Big Data Technologies. In: R. Luaces M., Karimipour F. (eds) Web and Wireless Geographical Information Systems. W2GIS 2018. Lecture Notes in Computer Science, vol 10819. Springer, Cham

Brisaboa, N. R.; Fariña, A.; Galaktionov, D.; Varela Rodeiro, T.; Rodríguez, M. : "New structures to solve aggregated queries for trips over public tranportation networks", en Proc. of the 25th Int. Symp. on String Proc. and Information Retrieval (SPIRE 2018) - LNCS 11147, Springer, Lima (Perú), 2018, pp. 85-98.

Brisaboa, N. R.; Gagie, T.; Gomez Brandon, A.; Navarro, G.: "Two-Dimensional Block Trees", en Proceedings of the 2018 Data Compression Conference (DCC 2018), IEEE Computer Society, Snowbird, Utah (Estados Unidos), 2018.

González Folgueira, L; Places, A. S. Pedreira, O.; Silva Coira, F: “Applying Variability Management in the Development of a Complex SaaS System: Real Experience and Findings”, en 14th International Conference on Web Information Systems and Technologies (WEBIST) http://insticc.org/node/TechnicalProgram/webist/personDetails/9F60CAD8-8E84-47F5-9755-4BF7F20C61AA

Artículos en revistas internacionales

David VilaresMiguel A. Alonso and Carlos Gómez-RodríguezSupervised Sentiment Analysis in Multilingual EnvironmentsInformation Processing & Management, 53(3):595-607, 2017. ISSN 0306-4573. DOI 10.1016/j.ipm.2017.01.004

David VilaresCarlos Gómez-Rodríguez and Miguel A. AlonsoUniversal, Unsupervised (Rule-Based), Uncovered Sentiment AnalysisKnowledge-Based Systems, 118:45-55, 2017. ISSN 0950-7051. DOI 10.1016/j.knosys.2016.11.014

L. Sanchez, N. Barreira, A. Mosquera, K. Evans, H. Pena-Verdeal, Defining the optimal region of interest for hyperemia grading in the bulbar conjunctiva, Computational and Mathematical Methods in Medicine, 2016, Article ID 3695014, 1-9, 2016.

Morán-Fernández, L., Bolón-Canedo, V., & Alonso-Betanzos, A. (2017). Can classification performance be predicted by complexity measures? A study using microarray data. Knowledge and Information Systems51(3), 1067-1090.

Morán-Fernández, L., Bolón-Canedo, V., & Alonso-Betanzos, A. (2017). Centralized vs. distributed feature selection methods based on data complexity measures. Knowledge-Based Systems117, 27-45.

Isaac Fernández-Varela, Elena Hernández-Pereira, Diego Álvarez-Estévez, Vicente Moret-Bonillo, Combining machine learning models for the automatic detection of EEG arousals, Neurocomputing, Volume 268, 2017, Pages 100-108, ISSN 0925-2312, http://dx.doi.org/10.1016/j.neucom.2016.11.086.

Isaac Fernández-Varela, Diego Alvarez-Estevez, Elena Hernández-Pereira, Vicente Moret-Bonillo, A simple and robust method for the automatic scoring of EEG arousals in polysomnographic recordings, Computers in Biology and Medicine, Volume 87, 2017, Pages 77-86, ISSN 0010-4825, http://dx.doi.org/10.1016/j.compbiomed.2017.05.011.

Seijo-Pardo, B., Bolón-Canedo, V., & Alonso-Betanzos, A. (2017). Testing Different Ensemble Configurations for Feature Selection. Neural Processing Letters, 1-24.

Morán-Fernández, L., Bolón-Canedo, V., & Alonso-Betanzos, A. (2017). On the use of different base classifiers in multiclass problems. Progress in Artificial Intelligence, 1-9.

Seijo-Pardo, B., Porto-Díaz, I., Bolón-Canedo, V., & Alonso-Betanzos, A. (2017). Ensemble feature selection: Homogeneous and heterogeneous approaches. Knowledge-Based Systems118, 124-139.

Capítulo de Libro

Beatriz Remeseiro, Noelia Barreira, Luisa Sanchez Brea, Lucia Ramos, Antonio Mosquera, Machine Learning Applied to Optometry Data, Advances in Biomedical Informatics, 2017.

Preprocessing in high dimensional datasets - Springer (referencia bibliográfica aínda non disponible).

Alonso-Betanzos, A., Bolón-Canedo, V., Eiras-Franco, C., Morán-Fernández, L. and Seijo-Pardo, B. Preprocessing in high dimensional datasets. In Dawn E. Holmes and Lakhmi C. Jain. (Eds.), Advances in Biomedical Informatics. Springer-Verlag, 2017.

Libro

Autores: Miguel Ángel Rodríguez Luaces, Alejandro Cortiñas Álvarez, Guillermo de Bernardo Roca Editado / Impreso por: Reprografía Noroeste, S. L. Fecha de edición: 11/2016 ISBN: 978-84-16294-37-4 Depósito Legal: C2085-2016

Otras publicaciones

Galaktionov H., Daniil; Luaces, M. R.; Places, A. S.: "Navigational Rule Derivation: An Algorithm To Determine The Effect Of Traffic Signs On Road Networks", en Proc. of the 20th Pacific Asia Conference on Information Systems (PACIS 2016), AIS Electronic Library (AISeL), Chiayi (Taiwán), 2016.

Brisaboa, N. R.; Gomez Brandon, A.; Navarro, G.; Paramá, J. R.: "GraCT: A Grammar based Compressed representation of Trajectories", en Proc. of the 23rd Int. Symp. on String Processing and Information Retrieval (SPIRE 2016) - LNCS 9954, Springer , Beppu (Xapón), 2016, pp. 218-230.

Brisaboa, N. R.; Fariña, A.; Galaktionov H., Daniil; Rodríguez, M. Andrea: "Compact Trip Representation over Networks", en Proc. of the 23rd Int. Symp. on String Processing and Information Retrieval (SPIRE 2016) - LNCS 9954, Springer, Beppu (Xapón), 2016, pp. 240-253.

Artículos en revistas internacionales

Eiras-Franco, C., Bolón-Canedo, V., Ramos, S., González-Domínguez, J., Alonso-Betanzos, A., & Touriño, J. (2016). Multithreaded and Spark parallelization of feature selection filters. Journal of Computational Science

Daniel Valcarce, Javier Parapar, Álvaro Barreiro. Item-Based Relevance Modelling of Recommendations for Getting Rid of Long Tail Products. Knowledge-Based Systems, vol. 103, pp. 41-51, 2016. DOI 10.1016/j.knosys.2016.03.021.

Jesús Vilares, Miguel A. Alonso, Yerai Doval and Manuel Vilares, Studying the Effect and Treatment of Misspelled Queries in Cross-Language Information Retrieval, Information Processing & Management, 52(4):646-657, 2016. ISSN 0306-4573. DOI 10.1016/j.ipm.2015.12.010

L. Sanchez, N. Barreira, N. Sanchez-Marono, A. Mosquera, C. Garcia Resua, M.J. Giraldez, On the development of conjunctival hyperemia computer-assisted diagnosis tools: Influence of feature selection and class imbalance in automatic gradings, Artificial Intelligence in Medicine, 71, 30-42, 2016.

Caamaño, P., Salgado, R., Bellas, F., & Duro, R. J. (2016). Introducing Synaptic Delays in the NEAT Algorithm to Improve Modelling in Cognitive Robotics. Neural Processing Letters43(2), 479-504.

Salgado, R., Prieto, A., Bellas, F., Calvo-Varela, L., & Duro, R. J. (2016). Motivational engine with autonomous sub-goal identification for the Multilevel Darwinist Brain. Biologically Inspired Cognitive Architectures17, 1-11.

Artículos en revistas nacionales

Yerai Doval, Carlos Gómez-Rodríguez and Jesús Vilares, Segmentación de palabras en español mediante modelos del lenguaje basados en redes neuronales, Procesamiento del Lenguaje Natural, 57:75-82, 2016. ISSN 1135-5948.

David Vilares and Miguel A. AlonsoA review on political analysis and social mediaProcesamiento del Lenguaje Natural, 56:13-23, 2016. ISSN 1135-5948.

Capítulo de Libro

J. de MouraJ. NovoM. OrtegaP. Charlón"3D retinal vessel tree segmentation and reconstruction with OCT images"Lecture Notes in Computer Science: Image Analysis and Recognition9730716-726SpringerISBN: 978-3-319-41500-0International Conference on Image Analysis and Recognition, ICIAR'1613/07/2016-15/07/2016Povoa de Varzim, Portugal July 2016

J. de MouraJ. NovoM. OrtegaN. BarreiraM. G. Penedo"Vessel Tree Extraction and Depth Estimation with OCT Images"Lecture Notes in Artificial Intelligence: Advances in Artificial Intelligence986823-33SpringerISSN: 0302-9743ISBN: 978-3-319-44635-610.1007/978-3-319-44636-317th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 201614/09/2016 - 16/09/2016Salamanca September 2016

Otras publicaciones

Brisaboa, N. R.Cerdeira-Pena, A.Lopez Lopez, N.Navarro, G.Penabad, M. R.Silva Coira, F.: "Efficient Representation of Multidimensional Data over Hierarchical Domains", en Proc. of the 23rd Int. Symp. on String Processing and Information Retrieval (SPIRE 2016) - LNCS 9954, Springer, Beppu (Xapón), 2016, pp. 191-203.

Artículos en revistas internacionales

A. Monteagudo and J. Santos. “Treatment analysis in a cancer stem cell context using a tumor growth model based on cellular automata”. PLOS ONE doi: 10.1371/journal.pone.0132306, 10 (7), 2015 (Impact Factor: 3.234).

J. Santos and A. Monteagudo. “Analysis of behaviour transitions in tumour growth using a cellular automaton simulation”. IET Systems Biology. doi: http://dx.doi.org/10.1049/iet-syb.2014.0015 9(3):75 – 87, 2015 (Impact Factor: 1.059).

Daniel Valcarce, Javier Parapar, Álvaro Barreiro. A Distributed Recommendation Platform for Big Data. Journal of Universal Computer Science, vol. 21(13), pp. 1810-1829, 2015. DOI 10.3217/jucs-021-13-1810.

David VilaresMiguel A. Alonso and Carlos Gómez-RodríguezA linguistic approach for determining the topics of Spanish Twitter messagesJournal of Information Science, 41(2): 127-145, 2015. ISSN 0165-5515. DOI 10.1177/0165551514561652

David VilaresMiguel A. Alonso and Carlos Gómez-RodríguezA syntactic approach for opinion mining on Spanish reviewsNatural Language Engineering, 21(1):139-163, 2015. ISSN 1351-3249. DOI 10.1017/S1351324913000181

David VilaresMike Thelwall and Miguel A. AlonsoThe megaphone of the people? Spanish SentiStrength for real-time analysis of political tweetsJournal of Information Science, 41(6):799-813, 2015. ISSN 0165-5515. DOI 10.1177/0165551515598926

David VilaresMiguel A. Alonso and Carlos Gómez-RodríguezOn the usefulness of lexical and syntactic processing in polarity classification of Twitter messagesJournal of the Association for Information Science and Technology (JASIST), 66(9):1799-1816, 2015. ISSN 2330-1635. DOI 10.1002/asi.23284

Capítulo de Libro

J.Santos and A. Monteagudo. “Tumor growth emergent behavior analysis based on cancer hallmarks and in a cancer stem cell context”. Emerging Trends in Computational Biology, Bioinformatics and Systems Biology. Q-N. Tran & H.R. Arabnia (Eds.) 2015 (In Press)

L. Sanchez, N. Barreira, H. Pena Verdeal, E. Yebra Pimentel, A novel framework for hyperemia grading based on artificial neural networks, Lecture Notes in Computer Science: Advances in Computational Intelligence (International Work Conference on Artificial Neural Networks, IWANN 2015), 9094, 263-275, 2015.

L. Sanchez, N. Barreira, A. Mosquera, C. Garcia Resua, E. Yebra Pimentel, Automatic Selection of Video Frames for Hyperemia Grading, Lecture Notes in Computer Science: Computer Aided Systems Theory, Revised Selected Papers EUROCAST 2015, 9520, 479 - 486, 2015.

Artículos en revistas internacionales

A. Monteagudo and J. Santos. “Studying the capability of different cancer hallmarks to initiate tumor growth using a cellular automaton simulation. Application in a cancer stem cell context”. Biosystems doi: 10.1016/j.biosystems.2013.11.001115, 115:46-58. 2014 (Impact Factor: 1.548).

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