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AI-Powered Healthcare System to Fight the COVID-19 Pandemic on Federated Learning

AI-Powered Healthcare System to Fight the COVID-19 Pandemic on Federated Learning

S. Gnanamurthy, S. Raguvaran, B. Suresh Kumar, C. Santhosh Kumar, M. S. Hemawathi
Copyright: © 2024 |Pages: 25
ISBN13: 9798369310823|EISBN13: 9798369310830
DOI: 10.4018/979-8-3693-1082-3.ch010
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MLA

Gnanamurthy, S., et al. "AI-Powered Healthcare System to Fight the COVID-19 Pandemic on Federated Learning." Federated Learning and AI for Healthcare 5.0, edited by Ahdi Hassan, et al., IGI Global, 2024, pp. 178-202. https://doi.org/10.4018/979-8-3693-1082-3.ch010

APA

Gnanamurthy, S., Raguvaran, S., Suresh Kumar, B., Santhosh Kumar, C., & Hemawathi, M. S. (2024). AI-Powered Healthcare System to Fight the COVID-19 Pandemic on Federated Learning. In A. Hassan, V. Prasad, P. Bhattacharya, P. Dutta, & R. Damaševičius (Eds.), Federated Learning and AI for Healthcare 5.0 (pp. 178-202). IGI Global. https://doi.org/10.4018/979-8-3693-1082-3.ch010

Chicago

Gnanamurthy, S., et al. "AI-Powered Healthcare System to Fight the COVID-19 Pandemic on Federated Learning." In Federated Learning and AI for Healthcare 5.0, edited by Ahdi Hassan, et al., 178-202. Hershey, PA: IGI Global, 2024. https://doi.org/10.4018/979-8-3693-1082-3.ch010

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Abstract

The COVID-19 pandemic has caused several healthcare-related problems around the world. The pandemic has highlighted the shortcomings of employing current digital healthcare tools to manage public health emergencies. As a result, the COVID-19 issue has forced countries and research organizations to reassess healthcare delivery solutions to continue supplies while people stay at home or practice social isolation. Innumerable works of fiction have attempted to anticipate stock market returns and volatility using AI and machine learning. There is a dearth of a comprehensive overview of the various research orientations, discoveries, methodological methods, and contributions in the field of AI applications in finance. This research replicates realistic scenarios using a real COVID-19 dataset and evaluates issues such as model repetition delays, assuring the model's reliability and applicability. According to research findings, using this technology will enable medical professionals to detect coronavirus disease, achieve multiparty involvement in training, and improve data protection.

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