Adversarial Deep Generative Techniques for Early Diagnosis of Neurological Conditions and Mental Health Practises
Theoretical Insights with Practical Applications
Buch in deiner Nähe kaufen
Beschreibung
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.
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.
Presents innovative applications of deep generative models to improve the early diagnosis of neurological disorders Provides cutting-edge techniques for diagnosing conditions like Alzheimer’s, Parkinson’s, epilepsy, multiple sclerosis Features rich illustrations, clear tables, and a didactic approach to simplify complex concepts
Autor*in
Abhishek Kumar
Themen in »Adversarial Deep Generative Techniques for Early Diagnosis of Neurological Conditions and Mental Health Practises«
Deep Generative Models Neurological Diagnosis Generative Adversarial Networks (GANs) Variational Autoencoders (VAEs) Autoregressive Models Deep Learning in Medicine Medical Imaging Analysis Early Diagnosis Techniques Alzheimer's Disease Detection Parkinson's Disease Detection Epilepsy Diagnosis Multiple Sclerosis Diagnosis CNNs in Medical Diagnostics RNNs in Healthcare Transformer Models in Medicine