Ear and Hearing health supported by eHealth solutions - eHEar

BackgroundOtitis media is a common diagnosis in primary health care and reason for antibiotic prescription in children. Over-diagnosis leads to unnecessary use of antibiotics and diagnostic accuracy needs to improve. Detection of ear disease can be missed due to diagnostic inaccuracy causing a lifelong handicap.

AimThe aim is to develop and implement Artificial intelligence-systems (1) for automated diagnosis of smartphone-based digital images of the tympanic membrane together with smartphone-based acoustic reflectometry and (2) to test these systems in a clinical setting primary health care.MethodPart 1Development and implementation of smartphone-based AI-system for detection of middle ear fluid and otits media diagnosis based on:digital images of the tympanic membrane – a retrospective studydigital images together with smartphone-based acoustic reflectometry – a prospective studyPart 2Testing the new smartphone-based AI-systems in a prospective clinical diagnostic accuracy study in primary health care on ≥400 children with suspected acute otitis media in Region Västerbotten, Västra Götaland and Skåne.Reference method: expert panel assessmentSignificanceArtificial intelligence for diagnosis of ear disease in primary health care using smartphones may improve diagnostic accuracy and access to diagnosis world-wide.

Improved diagnostic accuracy may lower antibiotic prescription rate and ascertain correct treatment for those who need it most.