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 prediction technique for heart disease based on long short term memory recurrent neural network Subject The topic of the resource Bi-directional long short term memory; Conditional random field; Heart disease prediction; Nae bayes; Support vector machine Description An account of the resource In recent years, heart disease is one of the leading cause of death for both women and men. So, heart disease prediction is considered as a significant part in the clinical data analysis. Standard data mining techniques like Support Vector Machine (SVM), Naive Bayes and other machine learning techniques used in the earlier research for heart disease prediction. These methods are not sufficient for effective heart disease prediction due to insufficient test data. In this research, Bi-directional Long Short Term Memory with Conditional Random Field (BiLSTM-CRF) has been proposed to increase the efficiency of heart disease prediction. The input medical data were analyzed in a bidirectional manner for effective analysis, and CRF provided the linear relationship between the features. The BiLSTMCRF method has been tested on the Cleveland dataset to analyze the performance and compared with existing methods. The results showed that the proposed BiLSTM-CRF outperformed the existing methods in heart disease prediction. The average accuracy of the proposed BiLSTM-CRF is 90.04%, which is higher than the existing methods. 2020 by the authors. Creator An entity primarily responsible for making the resource Manur M.; Pani A.K.; Kumar P. Source A related resource from which the described resource is derived International Journal of Intelligent Engineering and Systems, Vol-13, No. 2, pp. 31-39. Publisher An entity responsible for making the resource available Intelligent Network and Systems Society Date A point or period of time associated with an event in the lifecycle of the resource 2020-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.22266/ijies2020.0430.04" target="_blank" rel="noreferrer noopener">https://doi.org/10.22266/ijies2020.0430.04</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092497346&amp;doi=10.22266%2Fijies2020.0430.04&amp;partnerID=40&amp;md5=5aa662fa28fb9e0554cf56220c5b94bf" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092497346&amp;doi=10.22266%2fijies2020.0430.04&amp;partnerID=40&amp;md5=5aa662fa28fb9e0554cf56220c5b94bf</a> Rights Information about rights held in and over the resource All Open Access; Bronze Open Access Relation A related resource ISSN: 2185310X 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 Manur M., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India; Pani A.K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India; Kumar P., Department of Computer Science and Technology, Motihari College of Engineering, Bihar, India