Time-to-Birth Prediction Models and the Influence of Expert Opinions

  • Gilles VandewieleEmail author
  • Isabelle Dehaene
  • Olivier Janssens
  • Femke Ongenae
  • Femke De Backere
  • Filip De Turck
  • Kristien Roelens
  • Sofie Van Hoecke
  • Thomas Demeester
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11526)


Preterm birth is the leading cause of death among children under five years old. The pathophysiology and etiology of preterm labor are not yet fully understood. This causes a large number of unnecessary hospitalizations due to high–sensitivity clinical policies, which has a significant psychological and economic impact. In this study, we present a predictive model, based on a new dataset containing information of 1,243 admissions, that predicts whether a patient will give birth within a given time after admission. Such a model could provide support in the clinical decision-making process. Predictions for birth within 48 h or 7 days after admission yield an Area Under the Curve of the Receiver Operating Characteristic (AUC) of 0.72 for both tasks. Furthermore, we show that by incorporating predictions made by experts at admission, which introduces a potential bias, the prediction effectiveness increases to an AUC score of 0.83 and 0.81 for these respective tasks.


Preterm birth Clinical decision support eHealth 



This research is funded by imec, the PRETURN clinical trial (B670201836255, EC/2018/0609) and a Ph.D. SB fellow scholarship of FWO (1S31417N).


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Gilles Vandewiele
    • 1
    Email author
  • Isabelle Dehaene
    • 2
  • Olivier Janssens
    • 1
  • Femke Ongenae
    • 1
  • Femke De Backere
    • 1
  • Filip De Turck
    • 1
  • Kristien Roelens
    • 2
  • Sofie Van Hoecke
    • 1
  • Thomas Demeester
    • 1
  1. 1.IDLabGhent University – imecGhentBelgium
  2. 2.Department of Gynecology and ObstetricsGhent University HospitalGhentBelgium

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