Holdings: A Survey of Federated Learning From Data Perspective in the Healthcare Domain: Challenges, Methods, and Future Directions

A Survey of Federated Learning From Data Perspective in the Healthcare Domain: Challenges, Methods, and Future Directions

Recent advances in deep learning (DL) have shown that data-driven insights can be used in smart healthcare applications to improve the quality of life for patients. DL needs more data and diversity to build a more accurate system. To satisfy these requirements, more data need to be pooled at the cen...

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Bibliographic Details
Main Authors:	Taha Z.K., Yaw C.T., Koh S.P., Tiong S.K., Kadirgama K., Benedict F., Tan J.D., Balasubramaniam Y.A.L.
Other Authors:	57202301078
Format:	Article
Published:	Institute of Electrical and Electronics Engineers Inc. 2024
Subjects:	Energy federated learning non-independent identical distribution privacy and security Computer aided diagnosis Computer aided instruction Data privacy Deep learning Health care Industrial research Federated learning Health care application Independent identical distributions Medical services Non-independent identical distribution Privacy Privacy and security Security Internet of things
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A Survey of Federated Learning From Data Perspective in the Healthcare Domain: Challenges, Methods, and Future Directions

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