Overview
- Includes cutting-edge methods and protocols
- Provides step-by-step detail essential for reproducible results
- Contains key notes and implementation advice from the experts
- This volume is Open Access
Part of the book series: Neuromethods (NM, volume 197)
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Table of contents (32 protocols)
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Front Matter
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Machine Learning Fundamentals
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Front Matter
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Data
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Front Matter
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Keywords
About this book
This Open Access volume 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. In the Neuromethods series style, chapters include the kind of detail and key advice from the specialists needed to get successful results in your laboratory.
Comprehensive and cutting, Machine Learning for Brain Disorders is a valuable resource for researchers and graduate students who are new to this field, as well as experienced researchers who would like to further expand their knowledge in this area. This book will be useful to students and researchers from various backgrounds such as engineers, computer scientists, neurologists, psychiatrists, radiologists, and neuroscientists.
Editors and Affiliations
Bibliographic Information
Book Title: Machine Learning for Brain Disorders
Editors: Olivier Colliot
Series Title: Neuromethods
DOI: https://doi.org/10.1007/978-1-0716-3195-9
Publisher: Humana New York, NY
eBook Packages: Springer Protocols
Copyright Information: The Editor(s) (if applicable) and The Author(s) 2023
Hardcover ISBN: 978-1-0716-3194-2Published: 25 July 2023
Softcover ISBN: 978-1-0716-3197-3Published: 25 July 2023
eBook ISBN: 978-1-0716-3195-9Published: 24 July 2023
Series ISSN: 0893-2336
Series E-ISSN: 1940-6045
Edition Number: 1
Number of Pages: XXXI, 1047
Number of Illustrations: 33 b/w illustrations, 232 illustrations in colour
Topics: Neurosciences