A Machine Learning‐Based Approach for Classification of Alzheimer’s Disease and its Risk Prediction

Dementia, a clinical syndrome with progressive neurodegenerative disease, is one of the inevitable aging consequences. Alzheimer’s disease (AD) is the most common cause of dementia. Accurate detection and classification of Alzheimer’s disease alongside its conversion from Mild Cognitive Impairment (MCI) to AD at an early stage is of significant clinical importance. However, a reliable diagnosis with a multi‐label classification approach remains a challenging task. This study aimed to measure the effectiveness of machine learning algorithm integrated with feature importance techniques to constitutes a multi‐label classification of AD prediction for clinical practice.