This paper is in the following e-collection/theme issue:

Digital Health Reviews (1318) Mobile Health (mhealth) (2974) Decision Support for Health Professionals (1203) Clinical Information and Decision Making (1426)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/43006, first published .
Applications of Federated Learning in Mobile Health: Scoping Review

Applications of Federated Learning in Mobile Health: Scoping Review

Applications of Federated Learning in Mobile Health: Scoping Review

Authors of this article:

Tongnian Wang1 Author Orcid Image ;   Yan Du2 Author Orcid Image ;   Yanmin Gong3 Author Orcid Image ;   Kim-Kwang Raymond Choo1 Author Orcid Image ;   Yuanxiong Guo1 Author Orcid Image
Article Authors Cited by (12) Tweetations (4) Metrics

Journals

  1. Liang X, Zhao J, Chen Y, Bandara E, Shetty S. Architectural Design of a Blockchain-Enabled, Federated Learning Platform for Algorithmic Fairness in Predictive Health Care: Design Science Study. Journal of Medical Internet Research 2023;25:e46547 View
  2. Fan K, Xu C, Cao X, Jiao K, Mo W. Tri-branch feature pyramid network based on federated particle swarm optimization for polyp segmentation. Mathematical Biosciences and Engineering 2024;21(1):1610 View
  3. Wang T, Zhang K, Cai J, Gong Y, Choo K, Guo Y. Analyzing the Impact of Personalization on Fairness in Federated Learning for Healthcare. Journal of Healthcare Informatics Research 2024;8(2):181 View
  4. Al-masni M, Marzban E, Al-Shamiri A, Al-antari M, Alabdulhafith M, Mahmoud N, Abdel Samee N, Kadah Y. Gait Impairment Analysis Using Silhouette Sinogram Signals and Assisted Knowledge Learning. Bioengineering 2024;11(5):477 View
  5. Freitas J, Bischof O. Computational modeling of aging-related gene networks: a review. Frontiers in Applied Mathematics and Statistics 2024;10 View
  6. Belal Y, Ben Mokhtar S, Haddadi H, Wang J, Mashhadi A. Survey of Federated Learning Models for Spatial-Temporal Mobility Applications. ACM Transactions on Spatial Algorithms and Systems 2024;10(3):1 View
  7. Majeed A, Hwang S. A Multifaceted Survey on Federated Learning: Fundamentals, Paradigm Shifts, Practical Issues, Recent Developments, Partnerships, Trade-Offs, Trustworthiness, and Ways Forward. IEEE Access 2024;12:84643 View
  8. Manzoor H, Shabbir A, Chen A, Flynn D, Zoha A. A Survey of Security Strategies in Federated Learning: Defending Models, Data, and Privacy. Future Internet 2024;16(10):374 View
  9. Zhou Y, Wang J, Kong X, Wu S, Xie X, Qi H. Exploring Amplified Heterogeneity Arising From Heavy-Tailed Distributions in Federated Learning. IEEE Transactions on Mobile Computing 2024;23(12):11519 View
  10. Huang G, Wu Q, Li J, Chen X. IMFL-AIGC: Incentive Mechanism Design for Federated Learning Empowered by Artificial Intelligence Generated Content. IEEE Transactions on Mobile Computing 2024;23(12):12603 View