Automation Bias in Mammography:The Impact of Artificial Intelligence BI-RADS Suggestions on Reader Performance

Autor: Thomas Dratsch, Xue Chen, Mohammad Rezazade Mehrizi, Roman Kloeckner, Aline Mähringer-Kunz, Michael Püsken, Bettina Baeßler, Stephanie Sauer, David Maintz, Daniel Pinto dos Santos

Publikováno v: Dratsch, T, Chen, X, Mehrizi, M R, Kloeckner, R, Mähringer-Kunz, A, Püsken, M, Baeßler, B, Sauer, S, Maintz, D & dos Santos, D P 2023, ' Automation Bias in Mammography : The Impact of Artificial Intelligence BI-RADS Suggestions on Reader Performance ', Radiology, vol. 307, no. 4, e222176, pp. 1-9 . https://doi.org/10.1148/radiol.222176
Radiology, 307(4):e222176, 1-9. Radiological Society of North America Inc.

Background: Automation bias (the propensity for humans to favor suggestions from automated decision-making systems) is a known source of error in human-machine interactions, but its implications regarding artificial intelligence (AI)–aided mammogra

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https://research.vu.nl/en/publications/b6042501-c326-4c8e-8b8b-254042d11aff