Published on in Vol 9, No 6 (2021): June
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/26598, first published
.

Journals
- Chen Z, Li D, Zhu J, Zhang S. DACFL: Dynamic Average Consensus-Based Federated Learning in Decentralized Sensors Network. Sensors 2022;22(9):3317 View
- Prayitno , Shyu C, Putra K, Chen H, Tsai Y, Hossain K, Jiang W, Shae Z. A Systematic Review of Federated Learning in the Healthcare Area: From the Perspective of Data Properties and Applications. Applied Sciences 2021;11(23):11191 View
- Joshi M, Pal A, Sankarasubbu M. Federated Learning for Healthcare Domain - Pipeline, Applications and Challenges. ACM Transactions on Computing for Healthcare 2022;3(4):1 View
- Rani S, Kataria A, Kumar S, Tiwari P. Federated learning for secure IoMT-applications in smart healthcare systems: A comprehensive review. Knowledge-Based Systems 2023;274:110658 View
- Li S, Liu P, Nascimento G, Wang X, Leite F, Chakraborty B, Hong C, Ning Y, Xie F, Teo Z, Ting D, Haddadi H, Ong M, Peres M, Liu N. Federated and distributed learning applications for electronic health records and structured medical data: a scoping review. Journal of the American Medical Informatics Association 2023;30(12):2041 View
- Guzzo A, Fortino G, Greco G, Maggiolini M. Data and model aggregation for radiomics applications: Emerging trend and open challenges. Information Fusion 2023;100:101923 View
- Sharma S, Guleria K. A comprehensive review on federated learning based models for healthcare applications. Artificial Intelligence in Medicine 2023;146:102691 View
Books/Policy Documents
- Stripelis D, Ambite J. Artificial Intelligence for Personalized Medicine. View