DEVELOPING AN EFFECTIVE MACHINE LEARNING ALGORITHM SYSTEM IN THE EARLY DETECTION AND DIAGNOSIS OF ALZHEIMER’S DISEASE

Abstract

A broad term used to describe diseases and conditions that cause deterioration in memory, language, and other mental capacities sufficiently extreme to communicate with day-to-day existence is "dementia". Alzheimer's disease is the most well-known type of Dementia influencing the mind's parts. As per range, this disorder influences 6.2 million Americans and 5 million individuals in India matured 65 and more seasoned. In 2019, the latest year for which information is accessible, official passing declarations revealed 121,499 deaths from Promotion, Alzheimer's, the "6th driving reason for death in the nation". In this paper, we propose AI calculations like Decision trees (DT), SVM, Linear regression, and Naive Bayes determines Promotion at the beginning phase. The Alzheimer's Sickness Neuroimaging Drive (ADNI) and the Open Access Series of Imaging Examinations give informational collections used to identify the disease in its beginning phase. The datasets comprise longitudinal X-ray information (age, orientation, small-scale mental status, CDR). By taking into; account many variables in every strategy, for example, accuracy, F1 Score, Review, and explicitness are determined. The outcomes acquired 93.7% of the greatest precision for the DT Calculation.