Deep learning screening of otoscopic images for ENT referral: development, validation and deployment of NHREF OtoScan

Background. Middle and external ear disease is common and largely treatable, but accurate otoscopic interpretation requires training that is scarce outside specialist ENT services. Published deep learning models for otoscopy report high accuracy, yet most are optimised for closed set classification rather than the referral decision a non specialist actually makes, report uncalibrated probabilities, and do not report the near duplicate controls that video derived otoscopic datasets demand. We developed, validated and deployed a screening aid framed around referral rather than diagnosis. Methods

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