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 Diabetes mellitus prediction using machine learning within the scope of a generic framework Subject The topic of the resource Chronic diseases; Classification; Diabetes; Machine learning; Predictive modelling Description An account of the resource Artificial intelligence (AI) based automated disease prediction has recently taken a significant place in the field of health informatics. However, due to unavailability of real time large scale medical data, the dynamic learning of prediction models remains principally subsided. This paper, therefore proposes a dynamic predictive modelling framework for chronic diseases prediction in real-time. The framework premise suggests creation of a centralized patient-indexed medical database to dynamically train machine learning (ML) models and predict risk levels of chronic diseases in real time. In this study, comprehensive empirical evaluations to train seven state-of-the-art ML models for diabetes risk prediction are performed in context of phase 2 of the suggested framework. The selected optimal model can then be dynamically applied to predict diabetes in phase 3 of the framework. Various metrics such as accuracy, precision, Recall, F1-score and receiver operating characteristic (ROC) curve are employed for evaluating performances of the trained models. Parameter tunings using different type of kernels, different number of neighbors and estimators are rigorously performed in order to create a suggestive literature for healthcare prediction ecosystem. Comparative analysis indicates high prediction accuracies on diabetes test data records for neural network and support vector machine (SVM) models as compared to other applied models. 2023 Institute of Advanced Engineering and Science. All rights reserved. Creator An entity primarily responsible for making the resource Arora N.; Srivastava S.; Agarwal R.; Mehndiratta V.; Tripathi A. Source A related resource from which the described resource is derived Indonesian Journal of Electrical Engineering and Computer Science, Vol-32, No. 3, pp. 1724-1735. 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 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/IJEECS.V32.I3.PP1724-1735" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/IJEECS.V32.I3.PP1724-1735</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177867818&amp;doi=10.11591%2FIJEECS.V32.I3.PP1724-1735&amp;partnerID=40&amp;md5=bf02de101902fe8c482e5f5ac4c40e7a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177867818&amp;doi=10.11591%2fIJEECS.V32.I3.PP1724-1735&amp;partnerID=40&amp;md5=bf02de101902fe8c482e5f5ac4c40e7a</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 Arora N., Department of Computer Science, Kalindi College, University of Delhi, Delhi, India; Srivastava S., School of Sciences, Christ (Deemed to be University), Delhi NCR, Ghaziabad, India; Agarwal R., Department of Information Technology, Raj Kumar Goel Institute of Technology, Ghaziabad, India; Mehndiratta V., School of Sciences, Christ (Deemed to be University), Delhi NCR, Ghaziabad, India; Tripathi A., Department of Data Science and Engineering, Manipal University Jaipur, Jaipur, India