Deep Learning Approaches for Early Diagnosis of Neurodegenerative Diseases aspires to serve as a comprehensive resource that delves deep into the integration of deep learning methodologies with the intricate terrain of neuroscientific principles for the early detection of neurodegenerative disorders. This book is designed for audiences comprising researchers, clinicians, and professionals straddling the realms of neurology, artificial intelligence, machine learning, and biomedical engineering. It caters to the aspirations of graduate students and postdoctoral researchers engaged in unraveling the mysteries of neurodegenerative diseases. Industry veterans with an eye for developing diagnostic tools and technologies will find a treasure trove of wisdom within its pages. For those with a fervent passion for comprehending the multifaceted applications of deep learning in early disease detection and the desire to propel progress in the field, this book is an invaluable resource. Additionally, policymakers and healthcare administrators, resolute in their mission to enhance diagnostic practices and elevate patient care standards for neurodegenerative disorders, will find this publication both enlightening and thought-provoking.
Coverage:
The many academic areas covered in this publication include, but are not limited to:
•Alzheimer's Disease
•Artificial Intelligence
•Biomarkers
•Clinical Applications
•Deep Learning
•Diagnostic tools
•Disease Management
•Early Diagnosis
•Healthcare Innovation
•Interdisciplinary Collaboration
•Machine Learning
•Neurodegenerative Diseases
•Neuroimaging
•Neuroscience
•Parkinson's Disease
Coverage:
The many academic areas covered in this publication include, but are not limited to:
•Alzheimer's Disease
•Artificial Intelligence
•Biomarkers
•Clinical Applications
•Deep Learning
•Diagnostic tools
•Disease Management
•Early Diagnosis
•Healthcare Innovation
•Interdisciplinary Collaboration
•Machine Learning
•Neurodegenerative Diseases
•Neuroimaging
•Neuroscience
•Parkinson's Disease