Mobile application for diagnosing alzheimer's based on clinical dementia rating
Abstract
Alzheimer's is a neurodegenerative disease characterized by memory loss, impaired thinking abilities, and changes in behavior. It is the most common form of dementia, significantly affecting a person's ability to carry out daily activities. Statistics indicate that the number of individuals suffering from Alzheimer's worldwide continues to rise as the population ages. Diagnosing Alzheimer's is a complex process that typically requires a skilled medical team. One diagnostic tool that can be utilized is an MRI machine. Previous research focused on extracting features from MRI images taken from three different cross-sections: axial, coronal, and sagittal. Based on these three types of cross-sectional images, we developed a system to classify the severity of Alzheimer's. This paper focuses on creating an Alzheimer's classification system accessible through a mobile application. The results indicate that our system has a performance accuracy of 90% in classifying the severity of the disease.
Keywords
Alzeimer; Classification; Mobile application; MRI machine; Neurodegenerative
Full Text:
PDFDOI: http://doi.org/10.11591/ijeecs.v40.i3.pp1607-1617
Refbacks
- There are currently no refbacks.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES).