PhD in Computational Science

2022/2023

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.

Committees

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

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)
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 0
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 2.38
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
Period Value
Places offered
Number of places for new students entering PhD (IPD01)
2019/2020 20
Demand
Number of applicants for PhD admission (IPD02)
2019/2020 15
First-time enrollment
Number of first-time enrollment students in PhD (IPD03)
2019/2020 9
First-time enrollment by adaptation
Number of first-time enrollment students in the program or students coming from other studies in extinction (IPD03.1)
2019/2020 0
Total enrollment
Total number of students enrolled (IPD04)
2019/2020 38
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)
2019/2020 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)
2019/2020 18.42
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)
2019/2020 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)
2019/2020 73.68
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)
2019/2020 5.26
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)
2019/2020 21.05
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)
2019/2020 15.79
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)
2019/2020 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)
2019/2020 13.16
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)
2019/2020 88.89
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)
2019/2020 38.46
Total number of defended thesis
Total number of defended thesis linked to the programme (IPD18.1)
2019/2020 9
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)
2019/2020 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)
2019/2020 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)
2019/2020 0
Total number of tesis written in Galician
Total number of defended thesis linked to the programme written in Galician (IPD18.3.1)
2019/2020 0
Total number of tesis written in Spanish
Total number of defended thesis linked to the programme written in Spanish (IPD18.3.2)
2019/2020 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)
2019/2020 9
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)
2019/2020 1,634
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)
2019/2020 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)
2019/2020 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)
2019/2020 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)
2019/2020 33.33
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)
2019/2020 66.67
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)
2019/2020 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)
2019/2020 100
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)
2019/2020 5
Period Value
Places offered
Number of places for new students entering PhD (IPD01)
2018/2019 20
Demand
Number of applicants for PhD admission (IPD02)
2018/2019 14
First-time enrollment
Number of first-time enrollment students in PhD (IPD03)
2018/2019 9
First-time enrollment by adaptation
Number of first-time enrollment students in the program or students coming from other studies in extinction (IPD03.1)
2018/2019 0
Total enrollment
Total number of students enrolled (IPD04)
2018/2019 31
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)
2018/2019 44.44
Percentage of foreign students
Ratio between the number of foreign students enrolled and the total number of students enrolled in the programme (IPD06)
2018/2019 22.58
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)
2018/2019 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)
2018/2019 83.87
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)
2018/2019 12.9
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)
2018/2019 3.23
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)
2018/2019 16.13
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)
2018/2019 25.81
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)
2018/2019 83.33
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)
2018/2019 33.33
Total number of defended thesis
Total number of defended thesis linked to the programme (IPD18.1)
2018/2019 1
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)
2018/2019 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)
2018/2019 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)
2018/2019 0
Total number of tesis written in Galician
Total number of defended thesis linked to the programme written in Galician (IPD18.3.1)
2018/2019 0
Total number of tesis written in Spanish
Total number of defended thesis linked to the programme written in Spanish (IPD18.3.2)
2018/2019 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)
2018/2019 1
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)
2018/2019 1,647
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)
2018/2019 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)
2018/2019 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)
2018/2019 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)
2018/2019 0
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)
2018/2019 100
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)
2018/2019 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)
2018/2019 100
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)
2018/2019 7.69

theses

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
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},
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.
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.
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
Using Machine Learning to Predict the Users Ratings on TripAdvisor Based on Their Reviews
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
Daniel Valcarce, Alfonso Landin, Javier Parapar, and Álvaro Barreiro. 2019. Collaborative filtering embeddings for memory-based recommender systems. Engineering Applications of Artificial Intelligence, 85, 347–356. issn: 0952-1976. doi: 10.1016/j.engappai.2019.06.020
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.
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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