Machine Learning,
Edition 1 Methods and Applications to Brain DisordersEditors: Edited by Andrea Mechelli and Sandra Vieira
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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.
Key Features
- 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
About the author
Edited by Andrea Mechelli, Professor of Early Intervention in Mental Health at the Institute of Psychiatry, Psychology & Neuroscience, King’s College London, UK
and Sandra Vieira, Researcher at the Institute of Psychiatry, Psychology & Neuroscience, King’s College London, UK
Title Reviews
"This is a fantastic resource for researchers and clinicians interested in the application of artificial intelligence to brain disorders. The most up-to-date approaches are covered, using a rigorous yet accessible language. The step-by-step practical guide will be particularly useful to those taking their first steps in this field."—Qiyong Gong, MD, PhD
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