Adversarial Deep Generative Techniques for Early Diagnosis of Neurological Conditions and Mental Health Practises: Theoretical Insights With Practical Applications: 46 - Rilegato

 
9783031911460: Adversarial Deep Generative Techniques for Early Diagnosis of Neurological Conditions and Mental Health Practises: Theoretical Insights With Practical Applications: 46
Rilegato
ISBN 10: 3031911466 ISBN 13: 9783031911460
Casa editrice: Springer-Nature New York Inc, 2025

Sinossi

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.

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Dalla quarta di copertina

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Springer-Nature New York Inc
Data di pubblicazione
2025
Lingua
Inglese
ISBN 10 
3031911466
ISBN 13 
9783031911460
Rilegatura
Copertina rigida
Numero di pagine
428
Redattore
Kumar Abhishek, Ortiz-rodriguez Fernando, De Vasconcelos Jose Braga, Kumar Dutta Pushan, Saini Hemant Kumar
Contatto del produttore
Elevation
https://www.also.com/ec/cms5/en_6000/6000/index.jsp

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