A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a complication that can occur late in pregnancy. Preeclampsia is a sudden ...
A report in the Journal of Medical Internet Research shows developments in the evidence gap in drug safety during pregnancy in its News and Perspectives section. In "How Machine Learning Can Help ...
In a recent study uploaded to the medRxiv* pre-print server, researchers built and assessed machine learning models to predict depression in pregnant women using electronic medical record data. Their ...
Nearly 20% of pregnancies in people with lupus result in an adverse pregnancy outcome (APO). In a new study, scientists were able to improve prediction accuracy of APOs using machine learning. Machine ...
JMIR Publications today released a report on developments in the evidence gap in drug safety during pregnancy in its News and Perspectives section. In "How Machine Learning Can Help Close Evidence ...