5 papers
Embedding-Based Federated Learning with Runtime Governance for Iron Deficiency Prediction
Fan Zhang, Simon Deltadahl, Majid Lotfian Delouee +10
Recent reviews find that the vast majority of published healthcare federated learning (FL) studies never reach real-world deployment. We developed an embedding-based FL pipeline fo…
Building Privacy-and-Security-Focused Federated Learning Infrastructure for Global Multi-Centre Healthcare Research
Fan Zhang, Daniel Kreuter, Javier Fernandez-Marques +10
Collaborative healthcare research across multiple institutions increasingly requires diverse clinical datasets, but cross-border data sharing is strictly constrained by privacy reg…
SurvSurf: a partially monotonic neural network for first-hitting time prediction of intermittently observed discrete and continuous sequential events
Yichen Kelly Chen, Sören Dittmer, Kinga Bernatowicz +7
We propose a neural-network based survival model (SurvSurf) specifically designed for direct and simultaneous probabilistic prediction of the first hitting time of sequential event…
FedMAP: Personalised Federated Learning for Real Large-Scale Healthcare Systems
Fan Zhang, Daniel Kreuter, Carlos Esteve-Yagüe +11
Federated learning (FL) promises to enable collaborative machine learning across healthcare sites whilst preserving data privacy. Practical deployment remains limited by statistica…
Recent Methodological Advances in Federated Learning for Healthcare
Fan Zhang, Daniel Kreuter, Yichen Chen +10
For healthcare datasets, it is often not possible to combine data samples from multiple sites due to ethical, privacy or logistical concerns. Federated learning allows for the util…