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 Conference Papers Conference Paper Faculty Publications- Conference Papers 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 Machine Learning Algorithms for Stroke Risk Prediction Leveraging on Explainable Artificial Intelligence Techniques (XAI) Subject The topic of the resource Explain Like I'm Five (ELI5); Explainable Artificial Intelligence (XAI); Local Interpretable Model Agnostic Explanation (LIME); Machine Learning Description An account of the resource Stroke poses a significant global health challenge, contributing to widespread mortality and disability. Identifying predictors of stroke risk is crucial for enabling timely interventions, thereby reducing the increasing impact of strokes. This research addresses this imperative by employing Explainable Artificial Intelligence (XAI) techniques to pinpoint stroke risk predictors. To bridge existing gaps, six machine learning models were assessed using key performance metrics. Utilising the Synthetic Minority Over-sampling Technique (SMOTE) to minimize the impact of the imbalanced nature of the dataset used in this research, the Random Forest algorithm emerged as the most effective among the algorithms with an accuracy of 94.5%, AUC-ROC of 0.95, recall of 0.96, precision of 0.93, and an F1 score of 0.95. This study explored the interpretation of these algorithms and results using Local Interpretable Model-agnostic Explanations (LIME) and Explain Like I'm Five (ELI5). With the interpretations, healthcare providers can gain insight into patients' stroke risk predictions. Key stroke risk factors highlighted by the study include Age, Marital Status, Glucose Level, Body Mass Index, Work Type, Heart Disease, and Gender. This research significantly contributes to healthcare and healthcare informatics by providing insights that can enhance strategies for stroke prevention and management, ultimately leading to improved patient care. The identified predictors offer valuable information for healthcare professionals to develop targeted interventions, fostering a proactive approach to mitigating the impact of strokes on individuals and the healthcare system. 2024 IEEE. Creator An entity primarily responsible for making the resource Ugbomeh O.; Yiye V.; Ibeke E.; Ezenkwu C.P.; Sharma V.; Alkhayyat A. Source A related resource from which the described resource is derived 2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. 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/10.1109/ICEECT61758.2024.10739320" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICEECT61758.2024.10739320</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211172203&amp;doi=10.1109%2FICEECT61758.2024.10739320&amp;partnerID=40&amp;md5=2e43a5fb9306b35e3f01fa55e18d0efa" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211172203&amp;doi=10.1109%2fICEECT61758.2024.10739320&amp;partnerID=40&amp;md5=2e43a5fb9306b35e3f01fa55e18d0efa</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835037809-2 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 Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Ugbomeh O., Robert Gordon University, School of Creative and Cultural Business, Aberdeen, United Kingdom; Yiye V., Robert Gordon University, School of Creative and Cultural Business, Aberdeen, United Kingdom; Ibeke E., Robert Gordon University, School of Computing, Engrg.,and Tech, Aberdeen, United Kingdom; Ezenkwu C.P., Robert Gordon University, School of Computing, Engrg.,and Tech, Aberdeen, United Kingdom; Sharma V., Christ University, Computer Science Department, India; Alkhayyat A., Islamic University, College of Technical Engineering, Najaf, Iraq