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"This book examines the role of machine learning systems in the detection of neurological disorders such as Alzheimer disease, Parkinson's disease, schizophrenia, and depression"--Provided by publisher.
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Table of Contents
- Title Page
- Copyright Page
- Book Series
- Table of Contents
- Detailed Table of Contents
- Preface
- Chapter 1: Mapping the Intellectual Structure of the Field Neurological Disorders
- Chapter 2: Neurofeedback
- Chapter 3: Neurological Disorders, Rehabilitation, and Associated Technologies
- Chapter 4: Brain Tumor and Its Segmentation From Brain MRI Sequences
- Chapter 5: Early Detection of Parkinson's Disease
- Chapter 6: Soft Computing-Based Early Detection of Parkinson's Disease Using Non-Invasive Method Based on Speech Analysis
- Chapter 7: Assessment of Gait Disorder in Parkinson's Disease
- Chapter 8: Tremor Identification Using Machine Learning in Parkinson's Disease
- Chapter 9: Epileptic Seizure Detection and Classification Using Machine Learning
- Chapter 10: Neurocognitive Mechanisms for Detecting Early Phase of Depressive Disorder
- Chapter 11: Social Media Analytics to Predict Depression Level in the Users
- Chapter 12: Linguistic Markers in Individuals With Symptoms of Depression in Bi-Multilingual Context
- Chapter 13: Motor Imagery Classification Using EEG Signals for Brain-Computer Interface Applications
- Chapter 14: Intelligent Big Data Analytics in Health
- Chapter 15: Medical Image Segmentation
- Compilation of References
- About the Contributors
- Index
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