FedISM: Enhancing Data Imbalance via Shared Model in Federated Learning

Considering the sensitivity of data in medical scenarios, federated learning (FL) is suitable for applications that require data privacy. Medical personnel can use the FL framework for machine learning to assist in analyzing large-scale data that are protected within the institution. However, not al...

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Bibliographic Details

Published in:	Mathematics
Main Authors:	Wu-Chun Chung, Yan-Hui Lin, Sih-Han Fang
Format:	Article
Language:	English
Published:	MDPI AG 2023-05-01
Subjects:	federated learning shared model data imbalance Non-IID COVID-19
Online Access:	https://www.mdpi.com/2227-7390/11/10/2385