Electronic records predict premature babies' health risks - Futurity

You are free to share this article under the Attribution 4.0 International license. Using machine learning to sift through the electronic health records of both mothers and newborns can predict how premature babies will fare in their first two months of life, researchers report. The new method, reported in the journal Science Translational Medicine, allows physicians to classify, at or before birth, which infants are likely to develop complications of prematurity. "Preterm birth is the single largest cause of death in children under age 5 worldwide." "This is a new way of thinking about preterm birth, placing the focus on individual health factors of the newborns rather than looking only at how early they are born," says senior author Nima Aghaeepour, an associate professor of anesthesiology, perioperative and pain medicine and of pediatrics Stanford University School of Medicine.