Exploiting Domain Knowledge as Causal Independencies in Modeling Gestational Diabetes

Pac Symp Biocomput. 2023:28:359-370.

Abstract

We consider the problem of modeling gestational diabetes in a clinical study and develop a domain expert-guided probabilistic model that is both interpretable and explainable. Specifically, we construct a probabilistic model based on causal independence (Noisy-Or) from a carefully chosen set of features. We validate the efficacy of the model on the clinical study and demonstrate the importance of the features and the causal independence model.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Causality
  • Computational Biology
  • Diabetes, Gestational*
  • Female
  • Humans
  • Models, Statistical
  • Pregnancy