Artificial Intelligence Diagnostic Decision Support to Reduce Antimicrobial Prescriptions in Young Children With Colds

Ear infections are common in young children with cold symptoms, but they can be difficult to diagnose due to small ear canals, child movement, and limited viewing time. In this study, investigators will take photos of the eardrums of children 6-24 months of age with upper respiratory symptoms. The photos will be reviewed by imaging software enhanced with artificial intelligence (AI app) to determine whether the AI app changes how ear infections are diagnosed and treated. The AI app has undergone rigorous study and was found to be highly accurate; but how using this technology affects the diagnosis and treatment by clinicians has not been studied. This research may help improve diagnostic accuracy for ear infections and ensure antibiotics are prescribed only for those children who have definite ear infections.

NCT Number	NCT06876259
Lead Sponsor	Timothy Shope Collaborators: Merck Sharp & Dohme LLC
Conditions	Acute Otitis Media (AOM), Upper Respiratory Infection
Enrollment	300 participants
Start Date	2025-12-04
Primary Completion	2026-12-30 (estimated)
Study Completion	2027-07-01 (estimated)
Updated on ClinicalTrials.gov	2026-01-07