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 An enhanced predictive modelling framework for highly accurate non-alcoholic fatty liver disease forecasting Subject The topic of the resource Chronic diseases; Class imbalance Classification; NAFLD; Predictive modelling; SMOTE Description An account of the resource Non-alcoholic fatty liver disease (NAFLD) is a chronic medical ailment characterized by accumulation of excessive fat in the liver of non-alcoholic patients. In absence of any early visible indications, application of machine learning based predictive techniques for early prediction of NAFLD are quite beneficial. The objective of this paper is to present a complete framework for guided development of varied predictive machine learning models and predict NAFLD disease with high accuracy. The framework employs stepby-step data quality enhancement to medical data such as cleaning, normalization, data upscaling using SMOTE (for handling class imbalances) and correlation analysis-based feature selection to predict NAFLD with high accuracy using only clinically recorded identifiers. Comprehensive comparative analysis of prediction results of seven machine learning predictive models is done using unprocessed as well as quality enhanced data. As per the observed results, XGBoost, random forest and neural network machine learning models reported significantly higher accuracies with improved AUC and ROC values using preprocessed data in contrast to unprocessed data. The prediction results are also assessed on various quality metrics such as accuracy, f1-score, precision, and recall significantly support the need for presented methodologies for qualitative NAFLD prediction modelling. 2025 Institute of Advanced Engineering and Science. All rights reserved. Creator An entity primarily responsible for making the resource Arora N.; Srivastava S.; Tripathi A.; Gupta V. Source A related resource from which the described resource is derived Indonesian Journal of Electrical Engineering and Computer Science, Vol-37, No. 1, pp. 214-222. 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 2025-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/ijeecs.v37.i1.pp214-222" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/ijeecs.v37.i1.pp214-222</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208103725&amp;doi=10.11591%2Fijeecs.v37.i1.pp214-222&amp;partnerID=40&amp;md5=a84dd07cd6cbc135d7799a85e5a88d1e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208103725&amp;doi=10.11591%2fijeecs.v37.i1.pp214-222&amp;partnerID=40&amp;md5=a84dd07cd6cbc135d7799a85e5a88d1e</a> Rights Information about rights held in and over the resource Restricted 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 Arora N., Department of Computer Science, Kalindi College, University of Delhi, Delhi, India; Srivastava S., School of Sciences, Christ University, Bengaluru, India; Tripathi A., Department of Data Science and Engineering, Manipal University Jaipur, Jaipur, India; Gupta V., School of Sciences, Christ University, Bengaluru, India