Development and Validation of an Automated Classifier to Diagnose Acute Otitis Media in Children.

ABSTRACT:

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. Eligible participants included children who presented for sick visits or wellness visits.

Exposure

Otoscopic examina

SUBMITTER: Shaikh N 

PROVIDER: S-EPMC10985552 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature