Machine learning for brain disorders
- Author
- Olivier Colliot
- Publication Year
- 2023
- Publisher
- Springer
- Language
- English
- Document Type
- Book
- Faculty / Subject Heading
- Computer Science
- Download Book Read book
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.
Keywords: Machine learning / Biochemical markers / Data science / Electronic health records / Neurology / Neurosciences / Psychiatry / Deep learning / Brain disorders / Neural networks / Statistical learning / Neuroimaging / Clinical data / Biomarkers / Electronic health records / Mobile devices
