Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal Outcomes

no code implementations • 16 Oct 2023 • Tomas M. Bosschieter, Zifei Xu, Hui Lan, Benjamin J. Lengerich, Harsha Nori, Ian Painter, Vivienne Souter, Rich Caruana

The interpretability of the EBM models reveals surprising insights into the features contributing to risk (e. g. maternal height is the second most important feature for shoulder dystocia) and may have potential for clinical application in the prediction and prevention of serious complications in pregnancy.

Using Interpretable Machine Learning to Predict Maternal and Fetal Outcomes

no code implementations • 12 Jul 2022 • Tomas M. Bosschieter, Zifei Xu, Hui Lan, Benjamin J. Lengerich, Harsha Nori, Kristin Sitcov, Vivienne Souter, Rich Caruana

Most pregnancies and births result in a good outcome, but complications are not uncommon and when they do occur, they can be associated with serious implications for mothers and babies.

BIG-bench Machine Learning Interpretable Machine Learning