Validating and AI Software for Assessment of Children With Ear Concerns
Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age6-6
SponsorGlimpse Diagnostics, Inc.
About this trial
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.
Eligibility criteria
Qualifiers
Males and females aged 6 months to 6 years
Presenting to a pediatrician's office or urgent care with signs and symptoms of otitis media, including tugging at ears, ear pain, crying at night, refusing to lie flat, sleeping poorly, having a fever, having decreased appetite, and/or concern for hearing loss, regardless of previous diagnosis of AOM or OME.
Disqualifiers
History of craniofacial abnormality
PE tubes currently in place
Current otorrhea
Caretaker not having use of both hands and arms
Trial design
Treatments tested in this trial
- Not listed
Trial groups
No trial groups listed
Locations
Sponsors and collaborators
Glimpse Diagnostics, Inc.
Lead sponsor
National Institute for Biomedical Imaging and Bioengineering (NIBIB)
Collaborator
Clinical Research Strategies
Collaborator
Source ClinicalTrials.gov