Torrent details for "Kumar A. Adversarial...Techniques..Early Diagnosis..Neurological…" Log in to bookmark
Controls:
×
Report Torrent
Please select a reason for reporting this torrent:
Your report will be reviewed by our moderation team.
×
Report Information
Loading report information...
This torrent has been reported 0 times.
Report Summary:
| User | Reason | Date |
|---|
Failed to load report information.
×
Success
Your report has been submitted successfully.
Checked by:
Category:
Language:
None
Total Size:
14.6 MB
Info Hash:
A70858821B253EE284F582143AC7C71B1AB9F1D7
Added By:
Added:
July 25, 2025, 3:38 p.m.
Stats:
|
(Last updated: July 25, 2025, 3:40 p.m.)
| File | Size |
|---|---|
| Kumar A. Adversarial...Techniques..Early Diagnosis..Neurological Conditions 2025.pdf | 14.6 MB |
NOTE
SOURCE: Kumar A. Adversarial...Techniques..Early Diagnosis..Neurological Conditions 2025
-----------------------------------------------------------------------------------
COVER
-----------------------------------------------------------------------------------
MEDIAINFO
Textbook in PDF format This book explores a pioneering exploration of how deep generative models, including generative adversarial networks (GANs) and variational autoencoders (VAEs), renovating early neurological disorder detection. This book is a bridge between computational neuroscience and clinical neurology gaps, providing novel AI-driven methodologies for diagnosing conditions such as Alzheimer’s, Parkinson’s, epilepsy, and neurodevelopmental disorders. With a strong focus on neuroimaging, genomic data analysis, and biomedical informatics, the book equips researchers and practitioners with the tools to improve diagnostic accuracy and decision-making. It includes practical case studies, visual illustrations, and structured methodologies for training and validating deep learning models. Designed for neurologists, radiologists, data scientists, and AI researchers, this book is an essential resource for advancing precision medicine and next-generation healthcare innovation
×