Mobile application for diagnosing alzheimer's based on clinical dementia rating

Retno Supriyanti, Muhammad Putra Yubiksana, Bintang Abelian Mahardika Wijonarko, Yogi Ramadhani, Muhammad Syaiful Aliim, Mohammad Irham Akbar, Haris Budi Widodo, Wahyu Widanarto, Muhammad Alqaaf

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

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DOI: http://doi.org/10.11591/ijeecs.v40.i3.pp1607-1617

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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).

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