"AI Smartphone App Revolutionizes Ear Infection Diagnosis at UPMC"
A study developed an artificial intelligence decision-support tool to interpret videos of the tympanic membrane, achieving a sensitivity of 93.8% and specificity of 93.5% in diagnosing acute otitis media in children. The tool, trained using deep residual-recurrent neural networks, could enhance accuracy in primary care settings and aid in treatment decisions, potentially transforming otoscopy in pediatric care.