Deep Generative Models for Integrative Analysis of Alzheimer's Biomarkers

Abhishek Kumar, S Rakesh Kumar, N Gayathri

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English

IGI Global
01 November 2024

Diseases & disorders; Neurology & clinical neurophysiology; Database design & theory; Information architecture

Summary
Details

The integration of generative AI and deep learning techniques for Alzheimer's disease detection significantly impacts the research community by advancing diagnostic accuracy and providing a comprehensive understanding of the disease. By combining multiple data modalities, including imaging, genetics, and clinical data, researchers can improve diagnostic precision and develop personalized treatment strategies. Generative AI facilitates efficient data utilization through dataset augmentation, fostering innovation and collaboration across interdisciplinary fields. These methodologies forward the exploration of new diagnostic tools while expediting their application in clinical practice, benefiting patients through early detection and intervention. The incorporation of generative AI may enhance research capabilities, promote collaboration, and improve Alzheimer's disease management and patient outcomes. Deep Generative Models for Integrative Analysis of Alzheimer's Biomarkers explores the integration of deep generative models in disease diagnosis, biomarking, and prediction. It examines the use of tools like data analysis, natural language processing, and machine learning for effective Alzheimer's research. This book covers topics such as data analysis, biomedicine, and machine learning, and is a useful resource for computer engineers, biologists, scientists, medical professionals, healthcare workers, academicians, and researchers.

Edited by: Abhishek Kumar, S Rakesh Kumar, N Gayathri
Imprint: IGI Global
Dimensions: Height: 254mm, Width: 178mm, Spine: 30mm
Weight: 1.139kg
ISBN: 9798369364420
Pages: 536
Publication Date: 01 November 2024
Audience: General/trade , ELT Advanced
Format: Hardback
Publisher's Status: Active