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.
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