Potential of Federated Learning in Healthcare
Yan Hu, Ahmad Chaddad · 2023
Federated learning (FL) has emerged as a promising approach for training machine learning models on distributed data while preserving privacy specifically in the field of medical diagnosis. This paper provides a review of the applications of FL in healthcare, presents the standard FL training process, and suggests future research directions. Our analysis indicates that while FL has shown great potential, more work is needed to optimize its implementation in healthcare settings and ensure the reliability of FL models. Further investigation is necessary to fully realize the potential of FL to improve medical diagnosis.