Deep Learning Applications in Neuroinformatics

Nyhet

Advances, Methods, and Perspectives

Häftad, Engelska, 2026

2 249 kr

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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.

Consolidates scattered information on deep learning techniques in neuroimaging data analysis, facilitating access for researchers, practitioners, and students
Explores deep learning algorithms applied to various neuroimaging data types, including EEG, MRI, and PET scans
Highlights methodologies like CNNs and RNNs
Includes real-world case studies that demonstrate how deep learning enhances research and clinical applications, such as identifying biomarkers for Alzheimer's disease and stroke

Produktinformation

Utgivningsdatum2026-03-24
Mått191 x 235 x 18 mm
Vikt450 g
FormatHäftad
SpråkEngelska
Antal sidor364
FörlagElsevier Science
ISBN9780443414596

Tillhör följande kategorier

Biomedicinsk teknik inom Medicin
Biokemisk teknik inom Naturvetenskap och teknik
Artificiell intelligens inom Data och IT

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.

1. Introduction to Deep Learning in Neuroinformatics2. Fundamentals of Deep Learning in Neuroinformatics3. Data Preprocessing and Augmentation Techniques for Neuroinformatics4. Deep Learning for Alzheimer’s Disease and Mild Cognitive Impairment5. Deep Learning in Stroke Detection and Rehabilitation6. Deep Learning for Autism Spectrum Disorder7. Deep Learning in Epilepsy Detection and Management8. Deep Learning Applications in Parkinson’s Disease and Movement Disorders9. Deep Learning for Multiple Sclerosis10. Deep Learning in Traumatic Brain Injury (TBI)11. Deep Learning for Neurodevelopmental and Psychiatric Disorders12. Explainable AI in Neuroinformatics13. Transfer Learning and Domain Adaptation in Neuroinformatics14. Integrating Multi-Modal Neuroimaging and Signal Data with Deep Learning15. Conclusion and Future Perspectives