2 papers
cs.LG2026
Federated Deep Learning for Privacy-Preserving Cardiovascular Disease Risk Prediction
Hyunho Mo, Djura Smits, Mahlet A. Birhanu +4
Cardiovascular disease risk prediction models often rely on data from a single institution or centrally pooled datasets. Extending these models across institutions could be limited…
cs.LG2025
MyDigiTwin: A Privacy-Preserving Framework for Personalized Cardiovascular Risk Prediction and Scenario Exploration
Héctor Cadavid, Hyunho Mo, Bauke Arends +5
Cardiovascular disease (CVD) remains a leading cause of death, and primary prevention through personalized interventions is crucial. This paper introduces MyDigiTwin, a framework t…