Alzheimer’s disease Classification using various machine learning approaches: A Review

Alzheimer's disease (AD) is a neurodegenerative illness in which brain cells deteriorate and die. It is a chronic illness. It is an incurable condition that causes memory loss as it proceeds. This research focuses on a detailed investigation of Convolution Neural Network-based computer-aided diagnosis of Alzheimer's disease (CNN). An accurate Alzheimer's disease (AD) diagnosis is critical for patient’s treatment, especially in the early stages of the disease. Prior knowledge allows patients to take preventive treatments before irreversible brain damage starts to occur.The main objective of this study is to assess more effective and coherent machine learning strategies for Alzheimer's disease classification. The main machine learning approaches examined in this study are Support Vector Machine (SVM), Artificial Neural Networks (ANN), and Deep Learning (DL). From the different kinds of literature, it is observed that the Convolutional Neural Network surpasses other approaches to diagnosing neurological illnesses.