Do as AI say: susceptibility in deployment of clinical decision-aids

Do as AI say: susceptibility in deployment of clinical decision-aids

Artificial intelligence (AI) models for decision support have been developed for clinical settings such as radiology, but little work evaluates the potential impact of such systems. In this study, physicians received chest X-rays and diagnostic advice, some of which was inaccurate, and were asked to...

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Bibliographic Details
Main Authors: Gaube, Susanne (Author), Suresh, Harini (Author), Raue, Martina Julia (Author), Merritt, Alexander (Author), Berkowitz, Seth J. (Author), Lermer, Eva (Author), Coughlin, Joseph F (Author), Guttag, John V. (Author), Colak, Errol (Author), Ghassemi, Marzyeh (Author)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Center for Transportation & Logistics (Contributor), AgeLab (Massachusetts Institute of Technology) (Contributor)
Format: Article
Language:English
Published: Springer Science and Business Media LLC, 2021-04-12T19:22:25Z.
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