Assessing the medical reasoning skills of GPT-4 in complex ophthalmology cases.

Journal: The British journal of ophthalmology
Published Date:

Abstract

BACKGROUND/AIMS: This study assesses the proficiency of Generative Pre-trained Transformer (GPT)-4 in answering questions about complex clinical ophthalmology cases.

Authors

  • Daniel Milad
    Faculty of Medicine, University of Montreal, Montreal, QC, Canada; Department of Ophthalmology, Centre Hospitalier de l'Université de Montréal, Montreal, QC, Canada.
  • Fares Antaki
    Department of Ophthalmology, University of Montreal, Montreal, QC H3T 1J4, Canada.
  • Jason Milad
    Department of Software Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
  • Andrew Farah
    Faculty of Medicine, McGill University, Montreal, QC H3A 0G4, Canada.
  • Thomas Khairy
    Faculty of Medicine, McGill University, Montreal, QC H3A 0G4, Canada.
  • David Mikhail
    Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
  • Charles-Édouard Giguère
    Centre de recherche de l'Institut universitaire en santé mentale de Montréal, Montréal, Quebec, Canada.
  • Samir Touma
    Department of Ophthalmology, Université de Montréal, Montréal, QC, Canada.
  • Allison Bernstein
    Department of Ophthalmology, Université de Montréal, Montreal, Québec, Canada.
  • Andrei-Alexandru Szigiato
    Department of Ophthalmology, Hôpital du Sacré-Coeur de Montréal, Montreal, QC H4J 1C5, Canada.
  • Taylor Nayman
    Department of Ophthalmology, University of Montreal, Montreal, QC H3T 1J4, Canada.
  • Guillaume A Mullie
    Department of Ophthalmology, University of Montreal, Montreal, QC H3T 1J4, Canada.
  • Renaud Duval
    Department of Ophthalmology, University of Montreal, Montreal, QC H3T 1J4, Canada.