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

ABSTRACT:

Background

The exponential growth of medical data and advancements in artificial intelligence (AI) have accelerated the development of data-driven health care. However, the secure and efficient sharing of sensitive medical data across institutions remains a major challenge due to privacy concerns, data silos, and regulatory restrictions. Traditional centralized systems are prone to data breaches and single points of failure, while existing privacy-preserving techniques face high computational and communication costs.

Objective

This study aims to provide a comprehensive review of the recent advances in blockchain-based federated learning (BCFL) within the medical field. By exploring the synergistic integration of federated learning and blockchain, this review evaluates how BC

SUBMITTER: Wang X 

PROVIDER: S-EPMC12919988 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature