104 citations · 217 across the 11 of their papers we have counts for
11 papers
An explainable framework for the relationship between dementia and glucose metabolism patterns
C. Vázquez-García, F. J. Martínez-Murcia, F. Segovia Román +6
High-dimensional neuroimaging data presents challenges for assessing neurodegenerative diseases due to complex non-linear relationships. Variational Autoencoders (VAEs) can encode…
Uncovering Neuroimaging Biomarkers of Brain Tumor Surgery with AI-Driven Methods
Carmen Jimenez-Mesa, Yizhou Wan, Guilio Sansone +7
Brain tumor resection is a highly complex procedure with profound implications for survival and quality of life. Predicting patient outcomes is crucial to guide clinicians in balan…
Tutorial: VAE as an inference paradigm for neuroimaging
C. Vázquez-García, F. J. Martínez-Murcia, F. Segovia Román +1
In this tutorial, we explore Variational Autoencoders (VAEs), an essential framework for unsupervised learning, particularly suited for high-dimensional datasets such as neuroimagi…
Statistical Agnostic Regression: a machine learning method to validate regression models
Juan M Gorriz, J. Ramirez, F. Segovia +3
Regression analysis is a central topic in statistical modeling, aimed at estimating the relationships between a dependent variable, commonly referred to as the response variable, a…
EEG Connectivity Analysis Using Denoising Autoencoders for the Detection of Dyslexia
Francisco Jesus Martinez-Murcia, Andrés Ortiz, Juan Manuel Górriz +4
The Temporal Sampling Framework (TSF) theorizes that the characteristic phonological difficulties of dyslexia are caused by an atypical oscillatory sampling at one or more temporal…
Convolutional Neural Networks for Neuroimaging in Parkinson's Disease: Is Preprocessing Needed?
Francisco J. Martinez-Murcia, Juan M. Górriz, Javier Ramírez +1
Spatial and intensity normalization are nowadays a prerequisite for neuroimaging analysis. Influenced by voxel-wise and other univariate comparisons, where these corrections are ke…
Revealing Patterns of Symptomatology in Parkinson's Disease: A Latent Space Analysis with 3D Convolutional Autoencoders
E. Delgado de las Heras, F. J. Martinez-Murcia, I. A. Illán +4
This work proposes the use of 3D convolutional variational autoencoders (CVAEs) to trace the changes and symptomatology produced by neurodegeneration in Parkinson's disease (PD). I…
Complex network modelling of EEG band coupling in dyslexia: an exploratory analysis of auditory processing and diagnosis
Nicolás J. Gallego-Molina, Andrés Ortiz, Francisco J. Martínez-Murcia +2
Complex network analysis has an increasing relevance in the study of neurological disorders, enhancing the knowledge of brain's structural and functional organization. Network stru…
Uncertainty-driven ensembles of deep architectures for multiclass classification. Application to COVID-19 diagnosis in chest X-ray images
Juan E. Arco, A. Ortiz, J. Ramirez +3
Respiratory diseases kill million of people each year. Diagnosis of these pathologies is a manual, time-consuming process that has inter and intra-observer variability, delaying di…
Dyslexia detection from EEG signals using SSA component correlation and Convolutional Neural Networks
Andrés Ortiz, Francisco J. Martinez-Murcia, Marco A. Formoso +2
Objective dyslexia diagnosis is not a straighforward task since it is traditionally performed by means of the intepretation of different behavioural tests. Moreover, these tests ar…
A Neural Approach to Ordinal Regression for the Preventive Assessment of Developmental Dyslexia
F. J. Martinez-Murcia, A. Ortiz, Marco A. Formoso +3
Developmental Dyslexia (DD) is a learning disability related to the acquisition of reading skills that affects about 5% of the population. DD can have an enormous impact on the int…