Machine Learning
Methods and Applications to Brain Disorders
- 408 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
About This Book
Machine Learning is an area of artificial intelligence involving the development of algorithms to discover trends and patterns in existing data; this information can then be used to make predictions on new data. A growing number of researchers and clinicians are using machine learning methods to develop and validate tools for assisting the diagnosis and treatment of patients with brain disorders. Machine Learning: Methods and Applications to Brain Disorders provides an up-to-date overview of how these methods can be applied to brain disorders, including both psychiatric and neurological disease. This book is written for a non-technical audience, such as neuroscientists, psychologists, psychiatrists, neurologists and health care practitioners.
- Provides a non-technical introduction to machine learning and applications to brain disorders
- Includes a detailed description of the most commonly used machine learning algorithms as well as some novel and promising approaches
- Covers the main methodological challenges in the application of machine learning to brain disorders
- Provides a step-by-step tutorial for implementing a machine learning pipeline to neuroimaging data in Python
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Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- Preface
- Part 1
- Part 2
- Part 3
- Part 4
- Glossary
- Index