Unravelling AI and Machine Learning Essentials in Alzheimer's Research-Reference-Cited by-同舟云学术

Unravelling AI and Machine Learning Essentials in Alzheimer's Research

Published:2024-06-28 Issue: Volume: Page:147-159
ISSN:2327-9354
Container-title:Advances in Medical Technologies and Clinical Practice
language:
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Author:

V. Saravanan¹^ORCID,Kalangi Ruth Ramya²,Thangavel Saravanan³,K. Venkata Ramana⁴

Affiliation:

1. Dambi Dollo University, Ethiopia

2. Koneru Lakshmaiah Education Foundation, India

3. M. Kumarasamy College of Engineering (Autonomous), India

4. QIS College of Engineering and Technology, India

Abstract

Artificial intelligence (AI) and system mastering (ML) have received a good-sized interest in Alzheimer's studies due to their capability to enhance prognosis and treatment. But a comprehensive know-how of these technologies and their software in Alzheimer's studies remains lacking. This review objectives to resolve the essentials of AI and ML in Alzheimer's studies, highlighting their capacity effect on sickness development and control. The results outline the modern-day nation of AI and ML use in Alzheimer's research and the challenges in their implementation, providing a foundation for additional improvements in this subject. The field of Alzheimer's studies has been greatly impacted by way of the fast improvement of artificial intelligence (AI) and system studying (ML) techniques. With a growing quantity of records being generated in this discipline and the need for more accurate predictions and remedies, AI and ML have come to be crucial gear for unraveling the complexities of Alzheimer's disease.

Publisher

IGI Global

Reference22 articles.

1. The Future of Precision Medicine in the Cure of Alzheimer’s Disease

2. . Ciurea, A. V., Mohan, A. G., Covache-Busuioc, R. A., Costin, H. P., Glavan, L. A., Corlatescu, A. D., & Saceleanu, V. M. (2023). Unraveling Molecular and Genetic Insights into Neurodegenerative Diseases. Advances in Understanding Alzheimer's, Parkinson's, ALS, and Huntington's Disease, 24.

3. EskandarK. (2023). Artificial Intelligence in Healthcare: Explore the Applications of AI in Various Medical Domains, Such as Medical Imaging, Diagnosis, Drug Discovery, and Patient Care., 4, 37–53.

4. Fan, Y., Song, Z., & Zhang, M. (2023). Emerging frontiers of artificial intelligence and machine learning in ischemic stroke: a comprehensive investigation of state-of-the-art methodologies, clinical applications, and unraveling challenges. EPMA Journal, 14, 645-661.

5. Artificial Intelligence in Medicine: A New Way to Diagnose and Treat Disease.;A. H.George;Partners Universal International Research Journal,2023