Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A novel two-tier feature selection model for Alzheimers disease prediction Subject The topic of the resource Hybrid regression models; Machine learning algorithms; neural network; Regression model; Statistical validation Description An account of the resource 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. Creator An entity primarily responsible for making the resource Maju S.V.; Pushpam G.P.O.S. Source A related resource from which the described resource is derived Indonesian Journal of Electrical Engineering and Computer Science, Vol-33, No. 1, pp. 227-235. Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/ijeecs.v33.i1.pp227-235" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/ijeecs.v33.i1.pp227-235</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184578040&amp;doi=10.11591%2Fijeecs.v33.i1.pp227-235&amp;partnerID=40&amp;md5=797901cdc6f140b45bb127bedca8a579" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184578040&amp;doi=10.11591%2fijeecs.v33.i1.pp227-235&amp;partnerID=40&amp;md5=797901cdc6f140b45bb127bedca8a579</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 25024752 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant 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