Adversarial Deep Generative Techniques for Early Diagnosis of Neurological Conditions and Mental Health Practises: Theoretical Insights with Practical ... Systems Engineering and Management, 46) - Hardcover
Synopsis
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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From the Back Cover
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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Adversarial Deep Generative Techniques for Early Diagnosis of Neurological Conditions and Mental Health Practises (Hardcover)
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ISBN 10: 3031911466
ISBN 13: 9783031911460
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Hardcover. Condition: new. Hardcover. 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 Alzheimers, Parkinsons, 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. mso-bidi-language: AR-SA;">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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9783031911460
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Adversarial Deep Generative Techniques for Early Diagnosis of Neurological Conditions and Mental Health Practises
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Springer, Berlin, Springer Nature Switzerland, Springer, 2025
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ISBN 13: 9783031911460
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 464 pp. Englisch. Seller Inventory # 9783031911460
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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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Buch. Condition: Neu. Adversarial Deep Generative Techniques for Early Diagnosis of Neurological Conditions and Mental Health Practises | Theoretical Insights with Practical Applications | Abhishek Kumar (u. a.) | Buch | x | Englisch | 2025 | Springer | EAN 9783031911460 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Seller Inventory # 133680114