Early Prediction of Alzheimer's Dementia Using Random Forest Machine Learning Algorithm: A Data-Driven Approach

Alzheimer's dementia is liberal neurological ailment categorized by memory loss, cerebral failure, and it is the utmost communal form of dementia and typically affects older adults. Every year, 6.7 million people are affecting by Alzheimer's dementia (AD) in USA and 4.3% probability of developing Alzheimer's ailment earlier the age of 65 in India. The principal issue associated with delayed prediction of Alzheimer's dementia lies in the incapacity to intervene during the formative years of the dementia progression, thereby missing opportunities for timely intervention and treatment. Available techniques for finding of Alzheimer's dementia with machine learning algorithms resulted in inability to predict the dementia early. For proactive diagnosis of Alzheimer's dementia, proposed a novel technique using Random Forest categorizer and also compared among various machine learning classifiers. Resulted in obtained accurate results with 97.5% of accuracy.