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  1. Home
  3. Securing Federated Learning With Blockchain In The Medical Field: Systematic Literature Review.
  1. Home
  3. Securing Federated Learning With Blockchain In The Medical Field: Systematic Literature Review.

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Securing Federated Learning With Blockchain in the Medical Field: Systematic Literature Review.

Xudong Wang1, Yi Xie2, Xiaoliang Chen1,3

  • 1Wuhan Union Hospital, 1277 Jiefang Avenue, Wuhan, Hubei Province, 430022, China, 86 1-397-121-3880.

Journal of Medical Internet Research
|February 19, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Blockchain-based federated learning (BCFL) offers secure medical data sharing and AI collaboration. This approach enhances privacy and mitigates risks in healthcare, paving the way for advanced smart health systems.

Keywords:
COVID-19Internet of Medical ThingsIoMTblockchainfederated learninghealth carehealth datareview

Related Experiment Videos

Area of Science:

  • Medical Informatics
  • Artificial Intelligence
  • Blockchain Technology

Background:

  • Exponential growth in medical data and AI necessitates secure data sharing.
  • Challenges include privacy concerns, data silos, and regulatory restrictions.
  • Centralized systems pose risks of data breaches and single points of failure.

Purpose of the Study:

  • To review recent advances in blockchain-based federated learning (BCFL) in medicine.
  • To evaluate how BCFL enhances data security and privacy in cross-institutional collaboration.
  • To explore BCFL applications in healthcare, including data sharing and telemedicine.

Main Methods:

  • Systematic literature review from 2018-2025.
  • Databases searched: PubMed, IEEE Xplore, Web of Science, Google Scholar.
  • Inclusion of over 100 high-quality papers covering BCFL foundations, architectures, and applications.

Main Results:

  • BCFL integrates blockchain's trust with federated learning's privacy.
  • Mitigates risks like model tampering and data leakage in federated systems.
  • Applications include medical data sharing, IoMT, epidemic forecasting, and telemedicine.

Conclusions:

  • BCFL is a transformative paradigm for secure, collaborative medical AI.
  • Combines decentralized trust, incentives, and privacy-enhancing machine learning.
  • Shows strong potential for precision medicine and global health data collaboration.