Nader Shaikh, Shannon J Conway, Jelena Kovacevic, Filipe Condessa, Timothy R Shope, Mary Ann Haralam, Catherine Campese, Matthew C Lee, Tomas Larsson, Zafer Cavdar, Alejandro Hoberman
IMPORTANCE: Acute otitis media (AOM) is a frequently diagnosed illness in children, yet the accuracy of diagnosis has been consistently low. Multiple neural networks have been developed to recognize the presence of AOM with limited clinical application. OBJECTIVE: To develop and internally validate an artificial intelligence decision-support tool to interpret videos of the tympanic membrane and enhance accuracy in the diagnosis of AOM. DESIGN, SETTING, AND PARTICIPANTS: This diagnostic study analyzed otoscopic videos of the tympanic membrane captured using a smartphone during outpatient clinic visits at 2 sites in Pennsylvania between 2018 and 2023...
March 4, 2024: JAMA Pediatrics