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 Investigation on Preserving Privacy of Electronic Medical Record using Split Learning Subject The topic of the resource Healthcare; Patient data; Privacy; Security; Split Learning Description An account of the resource Artificial Intelligence is deployed in multiple areas, including healthcare. Utmost research is done in AI enabled healthcare industry because of the demands like accurate result, data security, exact prediction, huge volume of data, etc. In conventional deep learning models, the training happens with the dataset that are stored in a single device. This requires a huge storage space and highly efficient machines to train the data. Usage of big data, demands for innovative models that can be deployed and used in confined storage. Split learning is one such collaborative distributed deep learning model that allows the data to be stored in a split fashion. Split learning supports desirable features like less storage, more privacy to raw data, ability to work with resource constraints, etc., making it suitable for storing electronic medical record of patients. This paper discusses the advantages of using split learning for healthcare, the possible configurations of split learning that supports data privacy in healthcare and finally discusses the open research challenges in implementing split learning for healthcare. 2024 The Authors. Published by Elsevier B.V. Creator An entity primarily responsible for making the resource Kiruthika M.; Kumar A.; Krishnasamy L.; Sarveshwaran V. Source A related resource from which the described resource is derived Procedia Computer Science, Vol-233, pp. 614-622. Publisher An entity responsible for making the resource available Elsevier B.V. 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/10.1016/j.procs.2024.03.251" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.procs.2024.03.251</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192433820&amp;doi=10.1016%2Fj.procs.2024.03.251&amp;partnerID=40&amp;md5=96f40b4d76e04e80ad703a12a76b9e4d" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192433820&amp;doi=10.1016%2fj.procs.2024.03.251&amp;partnerID=40&amp;md5=96f40b4d76e04e80ad703a12a76b9e4d</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 18770509 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 Kiruthika M., Department of Computational Intelligence, School of Computing, SRM Institute of Science and Technology, Tamilnadu, Kattankulathur, 603203, India; Kumar A., Punjab National Bank, New Delhi, 110075, India; Krishnasamy L., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Karnataka, Bengaluru, 560074, India; Sarveshwaran V., Department of Computational Intelligence, School of Computing, SRM Institute of Science and Technology, Tamilnadu, Kattankulathur, 603203, India