Publicaciones en colaboración con investigadores/as de Universidad de Málaga (10)

2023

  1. Applications of machine learning and deep learning in SPECT and PET imaging: General overview, challenges and future prospects

    Pharmacological Research, Vol. 197

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

    Information Fusion, Vol. 100

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

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

  4. Using Explainable Artificial Intelligence in the Clock Drawing Test to Reveal the Cognitive Impairment Pattern

    International Journal of Neural Systems, Vol. 33, Núm. 4

2022

  1. Analyzing Statistical Inference Maps Using MRI Images for Parkinson’s Disease

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

  2. Automatic Classification System for Diagnosis of Cognitive Impairment Based on the Clock-Drawing Test

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

  3. CAD System for Parkinson’s Disease with Penalization of Non-significant or High-Variability Input Data Sources

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

  4. Ensemble Learning Using Weighted Convolutional Neural Networks for Parkinson's Disease

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

  5. Evaluating Intensity Concentrations During the Spatial Normalization of Functional Images for Parkinson’s Disease

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

2020

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

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