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Gamified Crowdsourcing as a Novel Approach to Lung Ultrasound Data Set Labeling: Prospective Analysis

Gamified Crowdsourcing as a Novel Approach to Lung Ultrasound Data Set Labeling: Prospective Analysis

For concordances with respect to leave-one-out reference standards, an individual expert’s concordance was the proportion of their opinions that matched their respective set of leave-one-out reference standard labels (the set of labels excluding their own opinion), and the crowd concordance was the proportion of the 6 leave-one-out reference standard labels matched by the crowd consensus label. The overall crowd concordance was the average of the per-clip crowd concordances.

Nicole M Duggan, Mike Jin, Maria Alejandra Duran Mendicuti, Stephen Hallisey, Denie Bernier, Lauren A Selame, Ameneh Asgari-Targhi, Chanel E Fischetti, Ruben Lucassen, Anthony E Samir, Erik Duhaime, Tina Kapur, Andrew J Goldsmith

J Med Internet Res 2024;26:e51397