A Review on Machine Learning Approaches for Diagnosis of Alzheimer’s Disease and Mild Cognitive Impairment Based on Brain MRI

Abstract

Alzheimer’s disease is a progressive disease for which researchers have yet to discover the main cause, but believe it probably involves a combination of age-related changes in the brain, genetic, environmental and lifestyle factors. Alzheimer’s is an irreversible disease that still has no cure. Therefore, its early diagnosis is very important to prevent its progression. Developing Machine Learning algorithms in healthcare, especially in brain disorders such as Alzheimer’s disease, provides new opportunities for early diagnosis and recognition of important biomarkers. This paper presents an overview of advanced studies based on Machine Learning techniques for diagnosing Alzheimer’s disease and different stages of mild cognitive impairment based on magnetic resonance imaging (MRI) images in the last 10 years. Also, this paper comprehensively describes the commonly efficient Machine Learning algorithms in each stage of magnetic resonance imaging processing used in the papers, which can facilitate the comparison of algorithms with each other and provide insight into the impact of each technique on classification performance. This review can be a valuable resource to gain a new perspective on the various research methods used in recent studies on Alzheimer’s disease.