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Validating and AI Software for Assessment of Children With Ear Concerns

NCT07243093 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 658

Last updated 2025-11-21

No results posted yet for this study

Summary

The goal of this observational study is to determine if the Glimpse machine learning algorithm can accurately assess ear diseases in children. Participants will:

* Have a video of their ear taken by their parent or their guardian
* Have a video of their ear taken by a Primary Care Physician (PCP)
* Have an assessment of their eardrums and a video of their ears taken by an Ear, Nose, and Throat specialist (ENT).

The videos will be used to determine if the Glimpse algorithm matches the diagnosis of the physicians.

Conditions

  • Otalgia
  • Otitis Media
  • Otitis Media Effusion

Sponsors & Collaborators

  • National Institute for Biomedical Imaging and Bioengineering (NIBIB)

    collaborator NIH

  • Clinical Research Strategies

    collaborator UNKNOWN

  • Glimpse Diagnostics, Inc.

    lead INDUSTRY

Eligibility

Min Age
6 Months
Max Age
6 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-01-31
Primary Completion
2027-06-30
Completion
2027-07-31

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07243093 on ClinicalTrials.gov