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

Digital Health Reviews (1724) Mobile Health (mhealth) (3464) Decision Support for Health Professionals (1539) Clinical Information and Decision Making (1915)

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 (31) 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
  11. Vajrobol V, Singh S, Saxena G, Pundir A, Gaurav A, Bansal S, Attar R, Rahman M, Gupta B. A Comprehensive Survey on Federated Learning Applications in Computational Mental Healthcare. Computer Modeling in Engineering & Sciences 2025;142(1):49 View
  12. Rishu ., Kukreja V, Hariharan S, Dogra A, Goyal B. Information Modeling Technique to Decipher Research Trends of Federated Learning in Healthcare. The Open Neuroimaging Journal 2025;18(1) View
  13. Kapsecker M, Jonas S, Tsaneva-Atanasova K. Cross-device federated unsupervised learning for the detection of anomalies in single-lead electrocardiogram signals. PLOS Digital Health 2025;4(4):e0000793 View
  14. Yang M, Ngai E, Hu X, Hu B, Liu J, Gelenbe E, Leung V. Digital Phenotyping and Feature Extraction on Smartphone Data for Depression Detection. Proceedings of the IEEE 2024;112(12):1773 View
  15. Wu J, Ji H, Yi J, Liu L. Optimizing Client Selection in Federated Learning Base on Genetic Algorithm. Cluster Computing 2025;28(6) View
  16. Ma Z, Ruhaiyem N, Zhang M, Musa K, Hanis T, Xiao T, Hua D, Li H. A review of federated learning technology and its research progress in healthcare applications. Applied Intelligence 2025;55(10) View
  17. Wang J, Chen R, Long H, He J, Tang M, Su M, Deng R, Chen Y, Ni R, Zhao S, Rao M, Wang H, Tang L. Artificial intelligence in polycystic ovarian syndrome management: past, present, and future. La radiologia medica 2025;130(9):1409 View
  18. Ikegwu A, Alo U, Nweke H. Cyber threats in mobile healthcare applications: systematic review of enabling technologies, threat models, detection approaches, and future directions. Discover Computing 2025;28(1) View
  19. Naganna M, Ramachandra Nayaka G. Enhanced federated learning framework for handling heterogeneity in medical image data. Progress in Artificial Intelligence 2025 View
  20. Dhaouadi S, Khelifa M, Balti A, Duché P. Optical Sensor-Based Approaches in Obesity Detection: A Literature Review of Gait Analysis, Pose Estimation, and Human Voxel Modeling. Sensors 2025;25(15):4612 View
  21. Gill A, Desper D. Exploring Transformational Leaders in Driving Digital Health Innovation: Measuring and Sustaining Innovation Success. The Pinnacle: A Journal by Scholar-Practitioners 2025;3(2) View
  22. Chen Z, Liu R, Huang S, Guo Y, Ren Y. A Survey of Large-Scale Deep Learning Models in Medicine and Healthcare. Computer Modeling in Engineering & Sciences 2025;144(1):37 View
  23. Yang Y, Zhu S, Sun G, Zheng W. AHFL: A Resource-Adaptive Approach for Data-Heterogeneity-Aware Federated Learning. IEEE Internet of Things Journal 2025;12(23):50899 View
  24. Nadimi F, Abdisarabshali P, Borazjani K, Chakareski J, Hosseinalipour S. Multi-modal multi-task federated foundation models for next-generation extended reality systems: towards privacy-preserving distributed intelligence in AR/VR/MR. npj Wireless Technology 2025;1(1) View

Books/Policy Documents

  1. Chengxi H, Rajawat A, Goyal S, Solanki R. Intelligent Computing and Optimization. View
  2. Rimi H, Asaduzzaman M, Bhuiyan M, Shoaib H, Fuad K, Rahman M. Federated Learning in Health Care Technology. View

Conference Proceedings

  1. Negi V, Chinara S. 2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). Study of MobileNets Model in Federated Learning View
  2. Sharma A, Tripathi T, Majumdar A. 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). Enhancing Edge-based Cardiovascular Diagnosis through Federated Learning and IoT View
  3. Sharma P, Kashniyal J, ESham E. 2024 4th International Conference on Advancement in Electronics & Communication Engineering (AECE). An Insight into Federated Learning: A Collaborative Approach for Machine Learning View
  4. Seelam S, Doddipatla L, Upadhyay A, Pasam V, Pandey A, Gurajada H. 2025 International Conference on Innovations in Intelligent Systems: Advancements in Computing, Communication, and Cybersecurity (ISAC3). Federated Learning Framework for Privacy-Preserving Health Monitoring via IoT Devices View
  5. Yang G, Gong Y, Guo Y. Proceedings of the ACM/IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies. MIA: Masked Inpainting-Based Image Augmentation with Diffusion Models for Enhanced Dermatology Image Classification View