For healthcare datasets, it is often impossible to combine data samples from multiple sites
due to ethical, privacy, or logistical concerns. Federated learning allows for the utilization of …

Survival analysis is a fundamental tool in medicine, modeling the time until an event of
interest occurs in a population. However, in real-world applications, survival data are often …

Survival analysis is a subfield of statistics concerned with modeling the occurrence time of a
particular event of interest for a population. Survival analysis found widespread applications …

External control arms (ECA) can inform the early clinical development of experimental drugs
and provide efficacy evidence for regulatory approval. However, the main challenge in …

Most existing personalized federated learning approaches are based on intricate designs,
which often require complex implementation and tuning. In order to address this limitation …

This paper thoroughly investigates two major challenges faced by Federated Learning (FL):
high communication costs and adaptive requirements during the learning process. Based on …

Data preprocessing is a crucial step in machine learning that significantly influences model
accuracy and performance. In Federated Learning (FL), where multiple entities …