Novel Computer-Aided Diagnosis System for the Early Detection of Alzheimer’s Disease

Aging is a natural process that leads to debility, disease, and dependency. Alzheimer’s disease (AD) causes degeneration of the brain cells leading cognitive decline memory loss, as well dependence on others fulfill basic daily needs. AD major cause dementia. Computer-aided diagnosis (CADx) tools aid medical practitioners in accurately identifying diseases such patients. This study aimed develop CADx tool for early detection using Intelligent Water Drop (IWD) algorithm Random Forest (RF) classifier. The IWD an efficient feature selection method, was used identify most deterministic features dataset. RF ensemble method leverages multiple weak learners classify patient’s either demented (DN) or cognitively normal (CN). proposed also classifies patients mild impairment (MCI) CN. dataset which performance evaluated sourced from Disease Neuroimaging Initiative (ADNI). achieves 100% accuracy DN CN classification classifying MCI 92%. emphasizes significance pre-processing prior improve results tool.