Peer Learning and Artificial Intelligence in Radiology: Partners in Progress or Rivals in the Race for Accuracy?

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Bibliographic Details
Title: Peer Learning and Artificial Intelligence in Radiology: Partners in Progress or Rivals in the Race for Accuracy?
Authors: Kunst MM; UMass-Chan Medical School, Burlington, Massachusetts; Neuroradiology Section Head and Vice Chair of Faculty Affairs, UMass-Chan Lahey Department of Radiology. Electronic address: mara.m.kunst@lahey.org., Sharpe RE Jr; Consultant Division Chair, Breast Imaging, Department of Radiology, Mayo Clinic, Phoenix, Arizona., Wald C; Chair, Department of Radiology, UMass Chan-Lahey Lahey Hospital and Medical Center, Burlington, Massachusetts; Vice Chair, American College of Radiology Board of Chancellors; and Chair, IT Commission, American College of Radiology., Broder JC; UMass-Chan Medical School, Burlington, MA; and is Vice Chair of Quality and Safety, UMass-Chan Lahey Department of Radiology.
Source: Journal of the American College of Radiology : JACR [J Am Coll Radiol] 2025 Aug; Vol. 22 (8), pp. 961-963. Date of Electronic Publication: 2025 Apr 08.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: United States NLM ID: 101190326 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1558-349X (Electronic) Linking ISSN: 15461440 NLM ISO Abbreviation: J Am Coll Radiol Subsets: MEDLINE; In Process
Database: MEDLINE Ultimate
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