Publications (25) Publications in which a researcher has participated

filter_list Quantitative Biology

2024

  1. A Cross-Modality Latent Representation for the Prediction of Clinical Symptomatology in Parkinson’s Disease

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Enhancing Neuronal Coupling Estimation by NIRS/EEG Integration

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  3. Machine learning in small sample neuroimaging studies: Novel measures for schizophrenia analysis

    Human Brain Mapping, Vol. 45, Núm. 5

  4. Unraveling Brain Synchronisation Dynamics by Explainable Neural Networks using EEG Signals: Application to Dyslexia Diagnosis

    Interdisciplinary Sciences - Computational Life Sciences, Vol. 16, Núm. 4, pp. 1005-1018

  5. Visualizing Brain Synchronization: An Explainable Representation of Phase-Amplitude Coupling

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2022

  1. Automatic Diagnosis of Schizophrenia in EEG Signals Using Functional Connectivity Features and CNN-LSTM Model

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Complex network modeling of EEG band coupling in dyslexia: An exploratory analysis of auditory processing and diagnosis

    Knowledge-Based Systems, Vol. 240

  3. Quantifying Inter-hemispheric Differences in Parkinson’s Disease Using Siamese Networks

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2021

  1. Automatic Diagnosis of Schizophrenia in EEG Signals Using CNN-LSTM Models

    Frontiers in Neuroinformatics, Vol. 15

  2. Temporal EigenPAC for Dyslexia Diagnosis

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2020

  1. Multivariate Pattern Analysis Techniques for Electroencephalography Data to Study Flanker Interference Effects

    International Journal of Neural Systems, Vol. 30, Núm. 7

2019

  1. A Machine Learning Approach to Reveal the NeuroPhenotypes of Autisms

    International Journal of Neural Systems, Vol. 29, Núm. 7

  2. Comparison Between Affine and Non-affine Transformations Applied to I [ 123 ] -FP-CIT SPECT Images Used for Parkinson’s Disease Diagnosis

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  3. Genome-wide association analysis of dementia and its clinical endophenotypes reveal novel loci associated with Alzheimer's disease and three causality networks: The GR@ACE project

    Alzheimer's and Dementia, Vol. 15, Núm. 10, pp. 1333-1347

  4. Multivariate Pattern Analysis of Electroencephalography Data in a Demand-Selection Task

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  5. Multivariate pattern analysis of electroencephalography data in a demand-selection task

    Understanding the Brain Function and Emotions: 8th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2019 Almería, Spain, June 3–7, 2019 Proceedings, Part I (Springer Suiza), pp. 403-411

2018

  1. Analysis of I[123]-Ioflupane SPECT intensity iso-surfaces to assist the diagnosis of Parkinsonism

    2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings

  2. Ensemble classification of heterogeneous biomarkers in the diagnosis of Parkinsonism

    2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings

2017

  1. Construction and analysis of weighted brain networks from SICE for the study of Alzheimer’s disease

    Frontiers in Neuroinformatics, Vol. 11

  2. Dynamical graph theory networks methods for the analysis of sparse functional connectivity networks and for determining pinning observability in brain networks

    Frontiers in Computational Neuroscience, Vol. 11