AI-guided eardrum photos to improve diagnosis of ear infections in infants

Intelligent Medical Assessment for Guiding Ear Infection Treatment

Not applicable Interventional University of Pittsburgh · NCT06876259

This will test an AI app that reads photos of infants' eardrums to see if it changes how doctors diagnose ear infections and prescribe antibiotics for children 6–24 months with cold symptoms.

Quick facts

PhaseNot applicable
Study typeInterventional
Enrollment300 (estimated)
Ages6 Months to 24 Months
SexAll
SponsorUniversity of Pittsburgh Academic / other
Locations2 sites (Pittsburgh, Pennsylvania and 1 other locations)
Trial IDNCT06876259 on ClinicalTrials.gov

What this trial studies

This is a 12-month, single-center, within-subject trial enrolling about 300 children aged 6–24 months who present with upper respiratory symptoms. Each child's ears will be photographed and reviewed both by a standard clinical exam and by an AI imaging app in a double-blind within-subject design, producing paired diagnoses. The primary outcome compares antimicrobial prescription rates using 150 paired image/clinician decisions, and secondary outcomes include the proportion of uninterpretable images and AOM diagnosis rates. Parents will record symptoms daily for 10 days in electronic diaries to track symptom resolution and side effects, with study staff contacting families if symptom scores rise by more than 20%.

Who should consider this trial

Good fit: Children aged 6–24 months with upper respiratory symptoms who are not currently taking antibiotics and who do not have tympanostomy tubes or purulent ear drainage are ideal candidates.

Not a fit: Children with ear tubes, visible purulent ear drainage, no upper respiratory symptoms, or those already on antimicrobials would not be eligible and are unlikely to benefit from this intervention.

Why it matters

Potential benefit: If successful, this approach could reduce unnecessary antibiotic prescriptions by improving diagnostic accuracy for ear infections in young children.

How similar studies have performed: Prior technical studies of AI eardrum classifiers have shown high diagnostic accuracy, but using such apps to change clinician prescribing in routine care remains largely untested.

Eligibility criteria

Show full inclusion / exclusion criteria
Inclusion Criteria:

* Age 6-24 months
* Presence of upper respiratory infection

Exclusion Criteria:

* No upper respiratory infection
* Otorrhea
* Tympanostomy tubes
* Currently taking antimicrobials

Where this trial is running

Pittsburgh, Pennsylvania and 1 other locations

Study contacts

How to participate

  1. Review the eligibility criteria above with your treating physician.
  2. Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
  3. Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions Acute Otitis MediaUpper Respiratory Infectionacute otitis mediadiagnosisartificial intelligencediagnostic classifierantimicrobial stewardship
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.