A Novel Bayesian Linear Regression Model for the Analysis of Neuroimaging Data

A Novel Bayesian Linear Regression Model for the Analysis of Neuroimaging Data

In this paper, we propose a novel Machine Learning Model based on Bayesian Linear Regression intended to deal with the low sample-to-variable ratio typically found in neuroimaging studies and focusing on mental disorders. The proposed model combines feature selection capabilities with a formulation...

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Bibliographic Details
Main Authors: Albert Belenguer-Llorens, Carlos Sevilla-Salcedo, Manuel Desco, Maria Luisa Soto-Montenegro, Vanessa Gómez-Verdejo
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Applied Sciences
Subjects:
Bayesian learning
neuroimaging
feature selection
kernel formulation
mental disorders
schizophrenia
Online Access:https://www.mdpi.com/2076-3417/12/5/2571

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