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The impact of inconsistent human annotations on AI driven clinical decision making

Abstract In supervised learning model development, domain experts are often used to provide the class labels (annotations). Annotation inconsistencies commonly occur when even highly experienced clinical experts annotate the same phenomenon (e.g., medical image, diagnostics, or prognostic status), d...

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Bibliografische gegevens
Hoofdauteurs: Aneeta Sylolypavan, Derek Sleeman, Honghan Wu, Malcolm Sim
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: Nature Portfolio 2023-02-01
Reeks:npj Digital Medicine
Online toegang:https://doi.org/10.1038/s41746-023-00773-3
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