Abstract
Federated learning (FL) is one of the leading paradigms of modern times with higher privacy guarantees than any other digital solution. Since its inception in 2016, FL has been rigorously investigated from multiple perspectives. Some of these perspectives are extensions of FL’s applications in different sectors, communication overheads, statistical heterogeneity problems, client dropout issues, the legitimacy of FL system results, privacy preservation, etc. Recently, FL is being increasingly used in the medical domain for multiple purposes, and many successful applications exist that are serving mankind in various ways. In this work, we describe the novel applications and challenges of the FL paradigm with special emphasis on the COVID-19 pandemic. We describe the synergies of FL with other emerging technologies to accomplish multiple services to fight the COVID-19 pandemic. We analyze the recent open-source development of FL which can help in designing scalable and reliable FL models. Lastly, we suggest valuable recommendations to enhance the technical persuasiveness of the FL paradigm. To the best of the authors’ knowledge, this is the first work that highlights the efficacy of FL in the era of COVID-19. The analysis enclosed in this article can pave the way for understanding the technical efficacy of FL in medical field, specifically COVID-19.
Subject
Artificial Intelligence,Computer Science Applications,Information Systems,Management Information Systems
Cited by
5 articles.
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1. Healthcare 5.0;Advances in Healthcare Information Systems and Administration;2023-12-18
2. Federated Learning-Based Techniques for COVID-19 Detection—A Systematic Review;IoT Based Control Networks and Intelligent Systems;2023-11-28
3. Federated Learning for Medical Images Analysis: A Meta Survey;2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech);2023-11-14
4. Technical Analysis of Data-Centric and Model-Centric Artificial Intelligence;IT Professional;2023-11
5. On the Adoption of Modern Technologies to Fight the COVID-19 Pandemic: A Technical Synthesis of Latest Developments;COVID;2023-01-16