Fig. 1: Experimental design and cohort overview of PEDeliveryTime.

Experiment Design Workflow: The discovery cohort was obtained from the University of Michigan Health System and a validation cohort of similar size and time was obtained from the University of Florida Health System. We constructed 4 predictive models: baseline and full models for all PE patients and baseline and full models for EOPE patients. The input variables in baseline models include patients’ demographics, lifestyle, comorbidities and medical history. The full models include additional laboratory tests and vital signs from within 5 days of PE diagnosis, in addition to the variables in the baseline models. We trained the Cox-nnet prognosis prediction model using 80% training from the discovery cohort, tested it on 20% hold-out data from the discovery cohort, and validated it using the validation cohort. We then built clinically informative models by reducing Cox-nnet features based on both their importance scores and significance levels. The models are examined by the importance scores of top features and stratified survival curves based on patient survival risks. We disseminated the feature-reduced, clinically informative models into a user-friendly web application for healthcare professionals to use. Created in BioRender. Garmire, L. (2025) https://BioRender.com/q52s989.