Boosting wisdom of the crowd for medical image annotation using training performance and task features
Eeshan Hasan,
Erik Duhaime,
Jennifer S. Trueblood
Abstract:A crucial bottleneck in medical artificial intelligence (AI) is high-quality labeled medical datasets. In this paper, we test a large variety of wisdom of the crowd algorithms to label medical images that were initially classified by individuals recruited through an app-based platform. Individuals classified skin lesions from the International Skin Lesion Challenge 2018 into 7 different categories. There was a large dispersion in the geographical location, experience, training, and performance of the recruited… Show more
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