Deep Learning Applications in Neuroinformatics
Advances, Methods, and Perspectives
Published on 24. March 2026
Book
Paperback/Softback
364 pages
978-0-443-41459-6 (ISBN)
Description
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.
More details
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
Professional and scholarly
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 236 mm
Width: 190 mm
Thickness: 18 mm
Weight
771 gr
ISBN-13
978-0-443-41459-6 (9780443414596)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Karthik Ramamurthy
Deep Learning Applications in Neuroinformatics
Advances, Methods, and Perspectives
E-Book
03/2026
Elsevier
€166.99
Available for download
Person
Dr. Karthik Ramamurthy obtained his Doctoral degree from Vellore Institute of Technology, India and Master's degree from Anna University, India. Currently, He serves as Associate Professor in the Research Centre for Cyber Physical Systems, Vellore Institute of Technology, Chennai. His research interest includes Artificial Intelligence, Deep Learning, Computer Vision, Digital Image Processing, and Medical Image Analysis. He has published around 80 papers in peer reviewed journals and conferences. He is an active reviewer for journals published by Elsevier, IEEE Springer and Nature.
Content
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
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