Evaluating Use of Generative Artificial Intelligence in Clinical Pathology Practice: Opportunities and the Way Forward.

Journal: Archives of pathology & laboratory medicine
PMID: 39384182

Abstract

CONTEXT.—: Generative artificial intelligence (GAI) technologies are likely to dramatically impact health care workflows in clinical pathology (CP). Applications in CP include education, data mining, decision support, result summaries, and patient trend assessments.

Authors

  • Peter McCaffrey
    University of Texas Medical Branch, Galveston, TX, USA. pemccaff@UTMB.EDU.
  • Ronald Jackups
    Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO. rjackups@path.wustl.edu.
  • Jansen Seheult
    the Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota (Seheult, Pritt).
  • Mark A Zaydman
    Department of Pathology & Immunology, Washington University School of Medicine, Campus Box 8118, 660 South Euclid Avenue, St Louis, MO 63110, USA.
  • Ulysses Balis
    Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
  • Harshwardhan M Thaker
    From the Departments of Pathology (McCaffrey, Thaker) and Radiology (McCaffrey), University of Texas Medical Branch, Galveston.
  • Hooman Rashidi
    Department of Pathology and Laboratory Medicine, UC Davis School of Medicine, CA.
  • Rama R Gullapalli
    Departments of Pathology and Chemical and Biological Engineering, University of New Mexico, Albuquerque, New Mexico.

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