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"We wanted to try out a bunch of different AI algorithms, feed them all the information, and then see what's the most accurate predictor of mortality we can get," said study co-author Abhinav Suri, a medical student at the University of California, Los Angeles.The researchers used a decade's worth of data from 3,751 hip fracture patients to train 10 machine learning algorithms. The resulting models provide a"mortality risk score.
The model may not change how doctors manage hip fractures, which almost always demand surgery. But it could help doctors counsel the family, or signal for a health care worker to recommend more frequent or intensive follow-up care. "Hip fracture is such an enormous public health issue. In truth, it really demands a preventive approach," said Cody C. Wyles, MD, an assistant professor of orthopedic surgery and clinical anatomy at the Mayo Clinic, who was not involved in the study.