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Bridging AI and Clinical Practice: Integrating Automated Sleep Scoring Algorithm with Uncertainty-Guided Physician Review.

Michal BechnyGiuliana MonachinoLuigi FiorilloJulia van der MeerMarkus H SchmidtClaudio L A BassettiAthina TzovaraFrancesca D Faraci
Published in: Nature and science of sleep (2024)
Inter-scorer variability limits the accuracy of the scoring algorithms to ~80%. By integrating an uncertainty estimation with U-Sleep, we enhance the review of predicted hypnograms, to align with the scoring taste of a responsible physician. Validated across ID and OOD data and various sleep-disorders, our approach offers a strategy to boost automated scoring tools' usability in clinical settings.
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