Assessing the diagnostic accuracy of ChatGPT-4 in the histopathological evaluation of liver fibrosis in MASH.

Journal: Hepatology communications
PMID: 40304570

Abstract

BACKGROUND: Large language models like ChatGPT have demonstrated potential in medical image interpretation, but their efficacy in liver histopathological analysis remains largely unexplored. This study aims to assess ChatGPT-4-vision's diagnostic accuracy, compared to liver pathologists' performance, in evaluating liver fibrosis (stage) in metabolic dysfunction-associated steatohepatitis.

Authors

  • Davide Panzeri
    Department of Physics, University of Milano-Bicocca, Milan, Italy.
  • Thiyaphat Laohawetwanit
    Division of Pathology, Chulabhorn International College of Medicine, Thammasat University, Pathum Thani, Thailand.
  • Reha Akpinar
    Department of Biomedical Sciences, Humanitas University, Milan, Italy.
  • Camilla De Carlo
    Department of Biomedical Sciences, Humanitas University, Milan, Italy.
  • Vincenzo Belsito
    Department of Pathology, IRCCS Humanitas Research Hospital, Milan, Italy.
  • Luigi Terracciano
    Department of Biomedical Sciences, Humanitas University, Milan, Italy.
  • Alessio Aghemo
    Department of Biomedical Sciences, Humanitas University, Milan, Italy.
  • Nicola Pugliese
    Department of Biomedical Sciences, Humanitas University, Milan, Italy.
  • Giuseppe Chirico
    Department of Physics, University of Milano-Bicocca, Milan, Italy.
  • Donato Inverso
    Division of Immunology, Transplantation and Infectious Diseases IRCCS San Raffaele Scientific Institute, Milan, Italy.
  • Julien Calderaro
    Department of Pathology, Henri Mondor University Hospital, Créteil, France.
  • Laura Sironi
    Department of Physics, University of Milano-Bicocca, Milan, Italy.
  • Luca Di Tommaso
    Department of Biomedical Sciences, Humanitas University, Milan, Italy.

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