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Measuring the impact of AI in the diagnosis of hospitalized patients

12.19.23 | JAMA Network

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About The Study: Although standard artificial intelligence (AI) models improve diagnostic accuracy, systematically biased AI models reduced diagnostic accuracy, and commonly used image-based AI model explanations did not mitigate this harmful effect in this multicenter randomized clinical vignette survey study involving hospitalist physicians, nurse practitioners, and physician assistants from 13 states.

Authors: Michael W. Sjoding, M.D., of the University of Michigan Medical School, and Jenna Wiens, Ph.D., of the University of Michigan, Ann Arbor, are the corresponding authors.

To access the embargoed study: Visit our For The Media website at this link https://media.jamanetwork.com/

(doi:10.1001/jama.2023.22295)

Editor’s Note: Please see the article for additional information, including other authors, author contributions and affiliations, conflict of interest and financial disclosures, and funding and support.

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How to Cite This Article

APA:
JAMA Network. (2023, December 19). Measuring the impact of AI in the diagnosis of hospitalized patients. Brightsurf News. https://www.brightsurf.com/news/LQ47YE68/measuring-the-impact-of-ai-in-the-diagnosis-of-hospitalized-patients.html
MLA:
"Measuring the impact of AI in the diagnosis of hospitalized patients." Brightsurf News, Dec. 19 2023, https://www.brightsurf.com/news/LQ47YE68/measuring-the-impact-of-ai-in-the-diagnosis-of-hospitalized-patients.html.