Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Ebtehal Ibrahim Al-Fairouz
Qassim University
Computer Science & IT Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Improvement of alzheimer disease diagnosis accuracy using ensemble methods Mohammed Abdullah Al-Hagery; Ebtehal Ibrahim Al-Fairouz; Norah Ahmed Al-Humaidan
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (80.682 KB) | DOI: 10.52549/ijeei.v8i1.1321

Abstract

Nowadays, there is a significant increase in the medical data that we should take advantage of that. The application of the machine learning via the data mining processes, such as data classification depends on using a single classification algorithm or those complained as ensemble models. The objective of this work is to improve the classification accuracy of previous results for Alzheimer disease diagnosing. The Decision Tree algorithm with three types of ensemble methods combined, which are Boosting, Bagging and Stacking. The clinical dataset from the Open Access Series of Imaging Studies (OASIS) was used in the experiments. The experimental results of the proposed approach were better than the previous work results. Where the Random Forest (Bagging) achieved the highest accuracy among all algorithms with 90.69%, while the lowest one was Stacking with 79.07%. All these results generated in this paper are higher in accuracy than that done before.
Co-Authors Mohammed Abdullah Al-Hagery Norah Ahmed Al-Humaidan