Publicaciones en colaboración con investigadores/as de University of Cambridge (14)

2023

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

    Information Fusion, Vol. 100

2022

  1. A Connection between Pattern Classification by Machine Learning and Statistical Inference with the General Linear Model

    IEEE Journal of Biomedical and Health Informatics, Vol. 26, Núm. 11, pp. 5332-5343

  2. Standardization of Agnostic Learning Techniques in Neuroimaging: a Case Study in EEG

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

2021

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

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

2020

  1. Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications

    Neurocomputing, Vol. 410, pp. 237-270

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

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

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

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

2019

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

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

2018

  1. Assessing mild cognitive impairment progression using a spherical brain mapping of magnetic resonance imaging

    Journal of Alzheimer's Disease, Vol. 65, Núm. 3, pp. 713-729

  2. Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares

    Journal of Neuroscience Methods, Vol. 302, pp. 47-57

2017

  1. A heavy tailed expectation maximization hidden markov random field model with applications to segmentation of MRI

    Frontiers in Neuroinformatics, Vol. 11

  2. A semi-supervised learning approach for model selection based on class-hypothesis testing

    Expert Systems with Applications, Vol. 90, pp. 40-49

  3. Case-Based Statistical Learning: A Non-Parametric Implementation with a Conditional-Error Rate SVM

    IEEE Access, Vol. 5, pp. 11468-11478

  4. Preprocessing of 18F-DMFP-PET data based on Hidden Markov random fields and the Gaussian distribution

    Frontiers in Aging Neuroscience, Vol. 9, Núm. OCT