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 Privacy-preserving federated learning in healthcare: Fundamentals, state of the art and prospective research directions Subject The topic of the resource Architecture; Collaborative learning; Federated Learning; Health care; Privacy Preservation Description An account of the resource Recent collaborations in medical diagnostic systems are based on data private collaborative learning using Federated Learning (FL). In this approach, multiple organizations train a machine-learning model at the same time eventually leading to global model generation. This paper reviews the fundamentals of FL and its evolution path in Healthcare. The objective of this review is to scope a wide variety of healthcare applications in FL. Exactly what research direction is moving in interesting for research communities to guide their future course. This review uniquely focuses on examining numerous FL-based healthcare implementations, detailing their core methodologies and performance metrics, which, to our knowledge, have not been previously available. Privacy-preserving collaborative distributed learning through federated learning in healthcare enhances research collaborations, thereby resulting in better-performing models. This comprehensive review will act as a valuable reference for researchers exploring new FL applications in the healthcare domain. 2024 IEEE. Creator An entity primarily responsible for making the resource Namitha T.N.; Raghavendra S.; Vinith R. Source A related resource from which the described resource is derived 2024 IEEE 3rd World Conference on Applied Intelligence and Computing, AIC 2024, pp. 1438-1443. 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/AIC61668.2024.10730929" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/AIC61668.2024.10730929</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210231969&amp;doi=10.1109%2FAIC61668.2024.10730929&amp;partnerID=40&amp;md5=98e86c7df937a22aea610003596951bb" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210231969&amp;doi=10.1109%2fAIC61668.2024.10730929&amp;partnerID=40&amp;md5=98e86c7df937a22aea610003596951bb</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038459-8 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 Namitha T.N., Christ (Deemed to Be University), Department of Cse, Bangalore, India; Raghavendra S., Christ (Deemed to Be University), Department of Cse, Bangalore, India; Vinith R., Amrita Vishwa Vidyapeetham, School of Artificial Intelligence, Coimbatore, India