Detection and Classification of Alzheimer’s Disease Using Deep Learning Technique
Author(s)
T. Sharmila Devi, Sivakumar J
Abstract
It is crucial that people with Alzheimer's disease (AD) receive a proper diagnosis to begin preventative action before irreparable brain damage develops. The vast majority of people who suffer from Alzheimer's disease (AD), a neurological condition that progresses, are older than 65. The area of interest (ROI) in the hippocampus has been extensively studied for several purposes, including neurological illness research, stress development monitoring, and memory function analysis. Moreover, a connection between Alzheimer's disease and hippocampus volume shrinkage is shown. On the other hand, several biomarkers are used in the diagnosis of AD, such as tau, phosphorylated tau, amyloid beta (aβ42) protein, and hippocampus volume atrophy. Even while much recent research has used computers to diagnose AD, congenital findings with the majority of the machine learning strategies.