ItemArticle

A novel two-tier feature selection model for Alzheimers disease prediction

Title
A novel two-tier feature selection model for Alzheimers disease prediction
Creator
Maju S.V.; Pushpam G.P.O.S.
Description
The interdisciplinary research studies of artificial intelligence in health sector is bringing drastic life saving changes in the healthcare domain. One such aspect is the early disease prediction using machine learning and regression algorithms. The purpose of this research is to improve the prediction accuracy of Alzheimers disease by analysing the correlation of unexplored Alzheimer causing diseases. The work proposes Chi square-lasso ridge linear (Chi-LRL) model, a new two-tier feature ranking model which recognizes the significance of including diabetes, blood pressure and body mass index as potential Alzhiemer predictive parameters. The newly added predictive parameters of Alzheimers disease were statistically verified along with the conventional prediction parameters using chi-square method (Chi) as Tier 1 and an embedded model of lasso, ridge and linear (LRL) Regression for feature ranking as Tier 2. The performance of the proposed Chi-LRL model with selected features were then analysed using machine learning algorithms for performance analysis. The result shows a noticeable performance by selecting eleven significant features and a 4.5% increase in the prediction accuracy of Alzheirmer disease. 2024 Institute of Advanced Engineering and Science. All rights reserved.
Source
Indonesian Journal of Electrical Engineering and Computer Science, Vol-33, No. 1, pp. 227-235.
Date
2024-01-01
Publisher
Institute of Advanced Engineering and Science
Subject
Hybrid regression models; Machine learning algorithms; neural network; Regression model; Statistical validation
Coverage
Maju S.V., Department of Computer Science and Engineering, Christ (Deemed to be University), Bangalore, India; Pushpam G.P.O.S., Department of Computer Science and Engineering, Christ (Deemed to be University), Bangalore, India
Rights
All Open Access; Gold Open Access
Relation
ISSN: 25024752
Format
Online
Language
English
Type
Article

Collection

Articles

Citation

Maju S.V.; Pushpam G.P.O.S., “A novel two-tier feature selection model for Alzheimers disease prediction,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/13732.

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