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Statistical Agnostic Regression: a machine learning method to validate regression models
Regression analysis is a central topic in statistical modeling, aiming to estimate the relationships between a dependent variable, commonly referred to as the response variable, and one or more independent variables, i. e., explanatory variables.
Revealing Patterns of Symptomatology in Parkinson's Disease: A Latent Space Analysis with 3D Convolutional Autoencoders
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).
Uncertainty-driven ensembles of deep architectures for multiclass classification. Application to COVID-19 diagnosis in chest X-ray images
Respiratory diseases kill million of people each year.
A Neural Approach to Ordinal Regression for the Preventive Assessment of Developmental Dyslexia
Developmental Dyslexia (DD) is a learning disability related to the acquisition of reading skills that affects about 5% of the population.
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