Machine Learning for Brain Disorders

Table of Contents

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   Book Overview
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   Chapter 1 A Non-technical Introduction to Machine Learning
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   Chapter 2 Classic Machine Learning Methods
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   Chapter 3 Deep Learning: Basics and Convolutional Neural Networks (CNNs)
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   Chapter 4 Recurrent Neural Networks (RNNs): Architectures, Training Tricks, and Introduction to Influential Research
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   Chapter 5 Generative Adversarial Networks and Other Generative Models
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   Chapter 6 Transformers and Visual Transformers
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   Chapter 7 Clinical Assessment of Brain Disorders
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   Chapter 8 Neuroimaging in Machine Learning for Brain Disorders
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    Chapter 9 Electroencephalography and Magnetoencephalography
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    Chapter 10 Working with Omics Data: An Interdisciplinary Challenge at the Crossroads of Biology and Computer Science
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    Chapter 11 Electronic Health Records as Source of Research Data
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    Chapter 12 Mobile Devices, Connected Objects, and Sensors
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    Chapter 13 Medical Image Segmentation Using Deep Learning
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    Chapter 14 Image Registration: Fundamentals and Recent Advances Based on Deep Learning
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    Chapter 15 Computer-Aided Diagnosis and Prediction in Brain Disorders
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    Chapter 16 Subtyping Brain Diseases from Imaging Data
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    Chapter 17 Data-Driven Disease Progression Modeling
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    Chapter 18 Computational Pathology for Brain Disorders
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    Chapter 19 Integration of Multimodal Data
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    Chapter 21 Reproducibility in Machine Learning for Medical Imaging
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    Chapter 22 Interpretability of Machine Learning Methods Applied to Neuroimaging
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    Chapter 23 A Regulatory Science Perspective on Performance Assessment of Machine Learning Algorithms in Imaging
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    Chapter 24 Main Existing Datasets for Open Brain Research on Humans
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    Chapter 25 Machine Learning for Alzheimer’s Disease and Related Dementias
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    Chapter 26 Machine Learning for Parkinson’s Disease and Related Disorders
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    Chapter 27 Machine Learning in Neuroimaging of Epilepsy
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    Chapter 28 Machine Learning in Multiple Sclerosis
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    Chapter 29 Machine Learning for Cerebrovascular Disorders
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    Chapter 30 The Role of Artificial Intelligence in Neuro-oncology Imaging
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    Chapter 32 Machine Learning and Brain Imaging for Psychiatric Disorders: New Perspectives