Developing Federated Time-to-Event Scores Using Heterogeneous Real-World Survival Data

S Li, Y Shang, Z Wang, Q Wu, C Hong, Y Ning… - arXiv preprint arXiv …, 2024 - arxiv.org
Survival analysis serves as a fundamental component in numerous healthcare applications,
where the determination of the time to specific events (such as the onset of a certain disease …

Federated Learning for Clinical Structured Data: A Benchmark Comparison of Engineering and Statistical Approaches

S Li, D Miao, Q Wu, C Hong, D D'Agostino, X Li… - arXiv preprint arXiv …, 2023 - arxiv.org
Federated learning (FL) has shown promising potential in safeguarding data privacy in
healthcare collaborations. While the term" FL" was originally coined by the engineering …

Evaluating the Efficacy of Federated Scoring Systems with Heterogeneous Electronic Health Records

Q Wu, S Li, D Miao, Y Shang, X Li, N Liu - The Second Tiny Papers Track at … - openreview.net
Federated learning in healthcare research has primarily focused on black-box models,
leaving a notable gap in interpretability crucial for clinical decision-making. While scoring …

[PDF][PDF] FedScore: A Privacy-Preserving Framework for Federated Scoring System Development

FL Most - researchgate.net
[1] Li, Siqi, et al.(2023). Federated and distributed learning applications for electronic health
records and structured medical data: a scoping review. Journal of the American Medical …