Rochester, Minn.-based Mayo Clinic researchers created an AI algorithm that can successfully analyze patterns of changes in women who are in labor.
Researchers used data from the Eunice Kennedy Shriver National Institute of Child Health and Human Development's multicenter Consortium on Safe Labor database to create a risk-prediction machine learning algorithm, according to an Aug. 30 press release.
The model was used to analyze more than 700 clinical and obstetric factors in 66,586 deliveries.
The AI algorithm was able to predict individualized risks during the labor process, including identifying whether a successful vaginal delivery will occur with good outcomes for mother and the baby.
"This is the first step to using algorithms in providing powerful guidance to physicians and midwives as they make critical decisions during the labor process," said Abimbola Famuyide, MD, an OB-GYN at Mayo Clinic and senior author of the study. "Once validated with further research, we believe the algorithm will work in real time, meaning every input of new data during an expectant woman's labor automatically recalculate the risk of adverse outcome. This may help reduce the rate of cesarean delivery, and maternal and neonatal complications."
Mayo Clinic is conducting validation studies to assess the outcomes of AI models after they were implemented in labor units.