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Adversarial Deep Generative Techniques for Early Diagnosis of Neurological Conditions and Mental Health Practises

Theoretical Insights with Practical Applications

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Éditeur :

Springer


Paru le : 2025-07-15



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Description

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.
Pages
415 pages
Collection
n.c
Parution
2025-07-15
Marque
Springer
EAN papier
9783031911460
EAN PDF
9783031911477
Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
41
Taille du fichier
14961 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
200,44 €
EAN EPUB
9783031911477
Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
41
Taille du fichier
33423 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
200,44 €

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