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Deep survival analysis for interpretable time-varying prediction of preeclampsia risk.

Braden W EberhardKathryn J GrayDavid W BatesVesela P Kovacheva
Published in: Journal of biomedical informatics (2024)
This work demonstrates a novel application of deep survival analysis in time-varying prediction of preeclampsia risk. Our results highlight the advantage of deep survival models compared to Cox Proportional Hazards models in providing personalized risk trajectory and demonstrating the potential of deep survival models to generate interpretable and meaningful clinical applications in medicine.
Keyphrases
  • free survival
  • pregnant women
  • human health