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Home / Archives / Volume-4 / Issue-1 / Article-5

Volume - 4 | Issue - 1 | march 2022

Early detection of Alzheimer’s: Modalities and Methods Open Access
M. Monisha  , K. M. Harshitha, N. H. Dhanalakshmi, Kokatam Sai Prakash Reddy, C. R. Nagarathna, M. Kusuma  348
Pages: 69-79
Cite this article
Monisha, M., K. M. Harshitha, N. H. Dhanalakshmi, Kokatam Sai Prakash Reddy, C. R. Nagarathna, and M. Kusuma. "Early detection of Alzheimer’s: Modalities and Methods." Journal of Artificial Intelligence and Capsule Networks 4, no. 1 (2022): 69-79
DOI
10.36548/jaicn.2022.1.005
Published
04 May, 2022
Abstract

Alzheimer’s disease belongs to the group of neurodegenerative diseases and is considered as one of the most destructive and severe diseases of the human nervous system. There is presently no quick and cost-effective method for routinely screening individuals of age 65 and older for Alzheimer's disease, the most prevalent type of neurodegenerative dementia. Over 5.2 million Americans already suffer from this condition, with the number anticipated to rise to 7.7 million by 2030. This paper discusses how the use of Machine learning concepts has upgraded the detection of Alzheimer's disease in the early stage.

Keywords

Alzheimer's disease Cognitive Normal predictive testing Positron emission tomography Support vector machine Machine learning

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