Alzheimer’s Disease Diagnosis from MRI

Abstract

Alzheimer's disease (AD) is a neurological disorder. It is the 6th biggest cause of morbidity and mortality, according to the latest statistics. Mild Alzheimer's, Moderate Alzheimer's, and Severe Alzheimer's are the three main phases of the illness. Despite the reality that the condition is incurable, early recognition can aid in the provision of necessary therapy, therefore preventing further brain tissue damage. Although technology have been used to identify Alzheimer's disease in a string of recent research, most machine detection approaches are bound by congenital findings. Early stages of Alzheimer's disease can be identified, but not foreseen, because prediction is only possible before the dementia reveals itself. Deep Learning (DL) is now a popular method for detecting Alzheimer's disease early on. We use two types of data to predict disease categories: csv data that includes features associated with cognitive tasks such as SES, MMSE, CDR, eTIV, nWBV, ASF, delay, hereditary, MOCA, SAGE, CDT and general information about patient such as gender, age, dominant hand, Education, drowsiness, visits. F1-score, precision, recall, and accuracy are computed for every approach to evaluate its performance.