Machine Learning for Brain Disorders

This work provides readers with an up-to-date and comprehensive guide to both methodological and applicative aspects of machine learning (ML) for brain disorders. The chapters in this book are organized into five parts. Part One presents the fundamentals of ML. Part Two looks at the main types of da...

Descripción completa

Detalles Bibliográficos
Otros Autores: Colliot, Olivier, editor (editor)
Formato: Libro electrónico
Idioma:Inglés
Publicado: New York : Springer US 2023.
Colección:Neuromethods.
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009762680706719
Descripción
Sumario:This work provides readers with an up-to-date and comprehensive guide to both methodological and applicative aspects of machine learning (ML) for brain disorders. The chapters in this book are organized into five parts. Part One presents the fundamentals of ML. Part Two looks at the main types of data used to characterize brain disorders, including clinical assessments, neuroimaging, electro- and magnetoencephalography, genetics and omics data, electronic health records, mobile devices, connected objects and sensors. Part Three covers the core methodologies of ML in brain disorders and the latest techniques used to study them. Part Four is dedicated to validation and datasets, and Part Five discusses applications of ML to various neurological and psychiatric disorders.
Descripción Física:1 online resource (1047 pages) : illustrations
Bibliografía:Includes bibliographical references and index.
ISBN:9781071631959