Machine Learning Models for Prediction of Maternal Hemorrhage and Transfusion: Model Development Study.

Background: Current postpartum hemorrhage (PPH) risk stratification is based on traditional statistical models or expert opinion. Machine learning could optimize PPH prediction by allowing for more complex modeling.

Objective: We sought to improve PPH prediction and compare machine learning and traditional statistical methods.

Who's Posting What? A Qualitative, Cross-Sectional Study Comparing Twitter and Instagram Patterns Between Health Care Professionals and Patients.

Importance: There is a paucity of evidence-based, physician-authored content available on social media. Data are lacking on physicians use of social media, including intended audience and content.

Objective: The aim of this study was to explore the patterns of Twitter and Instagram use for popular urogynecology hashtags between physicians, patients, and allied health professionals (AHPs).