AI model can help diagnose pediatric buckle fractures

A team of researchers led by Dr. John Zech of Columbia University in New York City designed and tested a deep-learning model for detecting wrist fractures in imaging of pediatric patients. The group found that the algorithm was highly accurate on its own but also helped residents improve their accuracy identifying fractures.

“Access to [AI] predictions significantly improved overall average resident accuracy in diagnosing from 80% to 93%,” Zech said.

Studies suggest missed fractures may account for up to 80% of diagnostic errors in emergency departments. Buckle fractures of the distal…