Machine Learning: Methods and Applications to Brain Disorders

Machine Learning is an area of artificial intelligence involving the development of algorithms to discover trends and patterns in existing data, and the use of this information to make predictions on new data. Over the past decade, the use of Machine Learning in the field of neuroscience has gained considerable attention demonstrating the potential value of this approach for optimizing diagnostic and prognostic decisions in patients with psychiatric and neurological conditions. Machine Learning in the Brain Sciences provides an up-to-date reference of the current research of machine learning and how these methods can be applied to clinical, psychological and neuroscientific data. This is the first reference book that bridges the gap between the methods of machine learning, both supervised and unsupervised techniques, and its applications to real-world cases. Provides an introduction to machine learning and applications to brain disordersIncludes detailed descriptions of deep learning technique, including neural networks and auto-encodersContains chapters on regression models including regression and classifications INDICE: PART 1: MACHINE LEARNING - BASIC CONCEPTS 1. Introduction to Machine Learning 2. Feature Extraction and Feature Selection 3. Assessing model performance 4. Potential applications of ML to brain disorders PART 2: MACHINE LEARNING - METHODS AND APPLICATIONS TO THE BRAIN SCIENCES 5. Regression models - regression 6. Regression models - classification 7. K-Nearest Neighbours 8. Support Vector Machine - Classification 9. Support Vector Machine - Regression 10. Multiple Kernel Learning 11. Deep learning: Deep Neural Network 12. Deep Learning: Convolutional Neural Networks 13. Deep Learning: Auto-encoders 14. Dimensionality Reduction with Principal Component Analysis 15. Cluster Analysis with K-Means PART 3: CHALLENGES AND FUTURE DIRECTIONS 16. Missing Data, Small Sample Sizes and Heterogeneity 17. Working with High Dimensional Data 18. Integrating Different Types of Data 19. Ethical Issues in the Application of ML to Brain Disorders

• ISBN: 978-0-12-815739-8
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 400
• Fecha Publicación: 01/11/2019
• Nº Volúmenes: 1
• Idioma: Inglés