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 Techniques in Predicting Heart Disease a Survey Subject The topic of the resource and random forest; decision tree; heart disease; logistic regression; support vector machine Description An account of the resource The heart serves an important role in living creatures. Diagnosis and forecast of cardiac illnesses demand greater precision, perfection, and accuracy because such tiny mistakes can lead to weariness and death. Numerous heart-related deaths have occurred, and the incidence rates have been rising over time. Predicting the development of heart disorders is important to work in the medical industry. Every month, many databases related to the patient are kept. The information gathered can be used to predict the occurrence of future diseases. This article gives an outline of cardiovascular diseases and modern treatments. Also, the focus of this research is to outline some current research on applying machine learning techniques to predict heart disease, analyze the many machine learning algorithms employed, and determine which technique(s) are useful and efficient. Artificial neural network (ANN), decision tree (DT), fuzzy logic, K-nearest neighbor (KNN), Naive bayes (NB), and support vector machine (SVM) are data mining and machine learning approaches used to predict cardiac disease. This paper includes an overview of the present method based on features, the algorithms are compared, and the most accurate algorithm is analyzed. 2022 IEEE. Creator An entity primarily responsible for making the resource Roy R.E.; Kulkarni P.; Kumar S. Source A related resource from which the described resource is derived Proceedings - 2022 IEEE World Conference on Applied Intelligence and Computing, AIC 2022, pp. 373-377. 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 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/AIC55036.2022.9848945" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/AIC55036.2022.9848945</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137786934&amp;doi=10.1109%2FAIC55036.2022.9848945&amp;partnerID=40&amp;md5=7abcd5062d96953ffe5411d2fbee12c4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137786934&amp;doi=10.1109%2fAIC55036.2022.9848945&amp;partnerID=40&amp;md5=7abcd5062d96953ffe5411d2fbee12c4</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-150905001-7 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 Roy R.E., Christ (Deemed to Be University), School of Engineering and Technology, Department of Computer Science and Engineering, Bangalore, 560074, India; Kulkarni P., Christ (Deemed to Be University), School of Engineering and Technology, Department of Computer Science and Engineering, Bangalore, 560074, India; Kumar S., Christ (Deemed to Be University), School of Engineering and Technology, Department of Computer Science and Engineering, Bangalore, 560074, India