Development of time to event prediction models using federated learning.

Journal: BMC medical research methodology
Published Date: May 26, 2025

Abstract

BACKGROUND: In a wide range of diseases, it is necessary to utilize multiple data sources to obtain enough data for model training. However, performing centralized pooling of multiple data sources, while protecting each patients' sensitive data, can require a cumbersome process involving many institutional bodies. Alternatively, federated learning (FL) can be utilized to train models based on data located at multiple sites.

Authors

  • Rasmus Rask Kragh Jørgensen
    Department of Hematology, Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark. Rasmus.rask@rn.dk.
  • Jonas Faartoft Jensen
    Department of Hematology, Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark.
  • Tarec El-Galaly
    Department of Hematology, Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark.
  • Martin Bøgsted
    Jorne L. Biccler, Lasse Hjort Jakobsen, Martin Bøgsted, and Tarec C. El-Galaly, Aalborg University Hospital and Aalborg University, Aalborg; Peter de Nully Brown, Copenhagen University Hospital, Copenhagen; Henrik Frederiksen, Odense University Hospital, Odense; Judit Jørgensen, Aarhus University Hospital, Aarhus; Denmark; Sandra Eloranta and Karin E. Smedby, Karolinska Institutet, Stockholm; Mats Jerkeman, Lund University, Lund; and Karin E. Smedby, Karolinska University Hospital, Solna, Sweden.
  • Rasmus Froberg Brøndum
  • Mikkel Runason Simonsen
    Department of Hematology, Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark.
  • Lasse Hjort Jakobsen
    Jorne L. Biccler, Lasse Hjort Jakobsen, Martin Bøgsted, and Tarec C. El-Galaly, Aalborg University Hospital and Aalborg University, Aalborg; Peter de Nully Brown, Copenhagen University Hospital, Copenhagen; Henrik Frederiksen, Odense University Hospital, Odense; Judit Jørgensen, Aarhus University Hospital, Aarhus; Denmark; Sandra Eloranta and Karin E. Smedby, Karolinska Institutet, Stockholm; Mats Jerkeman, Lund University, Lund; and Karin E. Smedby, Karolinska University Hospital, Solna, Sweden.

Keywords

External Resources

Popular Topics
Recent Journals