Publicaciones en las que colabora con FRANCISCO JESÚS MARTÍNEZ MURCIA (38)

2023

  1. Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends

    Information Fusion, Vol. 100

  2. Nonlinear Weighting Ensemble Learning Model to Diagnose Parkinson's Disease Using Multimodal Data

    International Journal of Neural Systems, Vol. 33, Núm. 8

2022

  1. Modelling the Progression of the Symptoms of Parkinsons Disease Using a Nonlinear Decomposition of 123I FP-CIT SPECT Images

    Artificial intelligence in neuroscience: Affective analysis and health applications: 9th international work-conference on the interplay between natural and artificial computation, IWINAC 2022, Puerto de la Cruz, Tenerife, Spain, May 31-June 3, 2022, proceedings, Part I (Springer Suiza), pp. 104-113

  2. Modelling the Progression of the Symptoms of Parkinsons Disease Using a Nonlinear Decomposition of 123I FP-CIT SPECT Images

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

  3. Multilevel Modelling of Parkinson's Disease Symptom Progression in 123I FP-CIT SPECT

    2022 IEEE NSS/MIC RTSD - IEEE Nuclear Science Symposium, Medical Imaging Conference and Room Temperature Semiconductor Detector Conference

  4. Quantifying Differences between Affine and Nonlinear Spatial Normalization of FP-CIT Spect Images

    International Journal of Neural Systems, Vol. 32, Núm. 5

2021

  1. Statistical Agnostic Mapping: A framework in neuroimaging based on concentration inequalities

    Information Fusion, Vol. 66, pp. 198-212

2020

  1. Autosomal dominantly inherited alzheimer disease: Analysis of genetic subgroups by machine learning

    Information Fusion, Vol. 58, pp. 153-167

  2. Expectation–Maximization algorithm for finite mixture of α-stable distributions

    Neurocomputing, Vol. 413, pp. 210-216

  3. Granger causality-based information fusion applied to electrical measurements from power transformers

    Information Fusion, Vol. 57, pp. 59-70

  4. Morphological Characterization of Functional Brain Imaging by Isosurface Analysis in Parkinson's Disease

    International Journal of Neural Systems, Vol. 30, Núm. 9

  5. Optimized one vs one approach in multiclass classification for early alzheimer's disease and mild cognitive impairment diagnosis

    IEEE Access, Vol. 8, pp. 96981-96993

  6. Studying the Manifold Structure of Alzheimer's Disease: A Deep Learning Approach Using Convolutional Autoencoders

    IEEE Journal of Biomedical and Health Informatics, Vol. 24, Núm. 1, pp. 17-26

2019

  1. Assisted diagnosis of parkinsonism based on the striatal morphology

    International Journal of Neural Systems, Vol. 29, Núm. 9

  2. Classification Improvement for Parkinson’s Disease Diagnosis Using the Gradient Magnitude in DaTSCAN SPECT Images

    Advances in Intelligent Systems and Computing

  3. 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)

  4. Comparison between affine and non-affine transformations applied to I[123]-FP-CIT SPECT images used for Parkinson’s disease diagnosis

    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. 379-388

  5. Deep Convolutional Autoencoders vs PCA in a Highly-Unbalanced Parkinson’s Disease Dataset: A DaTSCAN Study

    Advances in Intelligent Systems and Computing

  6. Periodogram Connectivity of EEG Signals for the Detection of Dyslexia

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

  7. Support Vector Machine Failure in Imbalanced Datasets

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