FRANCISCO JESÚS
MARTÍNEZ MURCIA
PROGRAMA RAMON Y CAJAL
DIEGO
CASTILLO BARNES
Investigador en el periodo 2022-2022
Publicaciones en las que colabora con DIEGO CASTILLO BARNES (38)
2023
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Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends
Information Fusion, Vol. 100
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Nonlinear Weighting Ensemble Learning Model to Diagnose Parkinson's Disease Using Multimodal Data
International Journal of Neural Systems, Vol. 33, Núm. 8
2022
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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
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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)
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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
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Quantifying Differences between Affine and Nonlinear Spatial Normalization of FP-CIT Spect Images
International Journal of Neural Systems, Vol. 32, Núm. 5
2021
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Statistical Agnostic Mapping: A framework in neuroimaging based on concentration inequalities
Information Fusion, Vol. 66, pp. 198-212
2020
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Autosomal dominantly inherited alzheimer disease: Analysis of genetic subgroups by machine learning
Information Fusion, Vol. 58, pp. 153-167
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Expectation–Maximization algorithm for finite mixture of α-stable distributions
Neurocomputing, Vol. 413, pp. 210-216
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Granger causality-based information fusion applied to electrical measurements from power transformers
Information Fusion, Vol. 57, pp. 59-70
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Morphological Characterization of Functional Brain Imaging by Isosurface Analysis in Parkinson's Disease
International Journal of Neural Systems, Vol. 30, Núm. 9
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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
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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
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Assisted diagnosis of parkinsonism based on the striatal morphology
International Journal of Neural Systems, Vol. 29, Núm. 9
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Classification Improvement for Parkinson’s Disease Diagnosis Using the Gradient Magnitude in DaTSCAN SPECT Images
Advances in Intelligent Systems and Computing
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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)
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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
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Deep Convolutional Autoencoders vs PCA in a Highly-Unbalanced Parkinson’s Disease Dataset: A DaTSCAN Study
Advances in Intelligent Systems and Computing
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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)
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Support Vector Machine Failure in Imbalanced Datasets
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)