Introduction to Generative Artificial Intelligence: Contextualizing the Future.

Journal: Archives of pathology & laboratory medicine
Published Date: Feb 1, 2025

Abstract

CONTEXT.—: Generative artificial intelligence (GAI) is a promising new technology with the potential to transform communication and workflows in health care and pathology. Although new technologies offer advantages, they also come with risks that users, particularly early adopters, must recognize. Given the fast pace of GAI developments, pathologists may find it challenging to stay current with the terminology, technical underpinnings, and latest advancements. Building this knowledge base will enable pathologists to grasp the potential risks and impacts that GAI may have on the future practice of pathology.

Authors

  • Rajendra Singh
  • Ji Yeon Kim
    Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 four), Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea.
  • Eric F Glassy
    Affiliated Pathologists Medical Group, Inc., Rancho Dominguez, California.
  • Rajesh C Dash
    Department of Pathology, Duke Health, Durham, North Carolina (Dash).
  • Victor Brodsky
    the Department of Pathology and Immunology, Washington University, St Louis, Missouri (Brodsky).
  • Jansen Seheult
    the Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota (Seheult, Pritt).
  • M E de Baca
    Sysmex America, Lincolnshire, Illinois (de Baca).
  • Qiangqiang Gu
    International Center for Quantum Materials, School of Physics, Peking University, Beijing 100871, China.
  • Shannon Hoekstra
    Information Services, College of American Pathologists, Northfield, Illinois (Hoekstra).
  • Bobbi S Pritt
    Department of Laboratory Medicine and Pathology, Mayo Clinic, Minneapolis, MN, USA.

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