Klappentext

Deep Learning Applications in Neuroinformatics: Advances, Methods, and Perspectives explores how deep learning revolutionizes neuroinformatics, covering the latest methods and applications of deep learning in analyzing neuroimaging data from EEG, MRI, PET, and more. The book addresses critical neurological disorders like Alzheimer’s disease, Mild Cognitive Impairment, Stroke, and Autism Spectrum Disorder, bridging the gap between neuroscience and artificial intelligence. It is an ideal resource for researchers, practitioners, and students with insights from leading experts.

Inhalt

1. Introduction to Deep Learning in Neuroinformatics
2. Fundamentals of Deep Learning in Neuroinformatics
3. Data Preprocessing and Augmentation Techniques for Neuroinformatics
4. Deep Learning for Alzheimer’s Disease and Mild Cognitive Impairment
5. Deep Learning in Stroke Detection and Rehabilitation
6. Deep Learning for Autism Spectrum Disorder
7. Deep Learning in Epilepsy Detection and Management
8. Deep Learning Applications in Parkinson’s Disease and Movement Disorders
9. Deep Learning for Multiple Sclerosis
10. Deep Learning in Traumatic Brain Injury (TBI)
11. Deep Learning for Neurodevelopmental and Psychiatric Disorders
12. Explainable AI in Neuroinformatics
13. Transfer Learning and Domain Adaptation in Neuroinformatics
14. Integrating Multi-Modal Neuroimaging and Signal Data with Deep Learning
15. Conclusion and Future Perspectives