Testing a deep learning algorithm for automatic detection of prenatal ultrasound for under-resourced communities

Abstract

In rural and under-resourced communities, the scarcity of ultrasound (US) imaging results in a considerable gap in perinatal healthcare. To increase access to US, we tested a new automated diagnostic framework performed without an experienced sonographer or interpreting provider for assessment of fetal biometry, fetal presentation, and placental position.