Machine Learning for Alzheimer’s Disease Detection Based on Neuroimaging techniques: A Review

Abstract

Disease detection became one of the most important applications, especially with the rapid development of artificial intelligence techniques in the medical field. Alzheimer’s disease is considered as one of the irreversible disorders that infect the human brain, where cognitive performance declined, gradually. This paper present and discuss machine learning approaches for Alzheimer’s disease detection based on the neuroimaging modalities. Based on the revision, it shows that the utilization of different modalities, the availability of the scans, and the optimization of machine learning architectures played the main role to devise an accurate detection method for Alzheimer’s disease.