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portada Deep Generative Models for Integrative Analysis of Alzheimer’s Biomarkers
Type
Physical Book
Publisher
Author
Year
2024
Language
English
Pages
538
Format
Paperback
Dimensions
25.4 x 17.8 cm
ISBN13
9798369364437

Deep Generative Models for Integrative Analysis of Alzheimer’s Biomarkers

Abhishek Kumar;N. Gayathri;S. Rakesh Kumar (Author) · IGI Global · Paperback

Deep Generative Models for Integrative Analysis of Alzheimer’s Biomarkers - Abhishek Kumar;N. Gayathri;S. Rakesh Kumar

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Synopsis "Deep Generative Models for Integrative Analysis of Alzheimer’s Biomarkers"

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.

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