Translating ophthalmic medical jargon with artificial intelligence: a comparative comprehension study.

Journal: Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
Published Date: Dec 9, 2024

Abstract

OBJECTIVE: Our goal was to evaluate the efficacy of OpenAI's ChatGPT-4.0 large language model (LLM) in translating technical ophthalmology terminology into more comprehensible language for allied health care professionals and compare it with other LLMs.

Authors

  • Michael Balas
  • Alexander J Kaplan
    Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, Ontario, Canada.
  • Kaisra Esmail
    Department of Ophthalmology, Alberta Health Services, Red Deer, AB, Canada.
  • Solin Saleh
    Department of Ophthalmology, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada.
  • Rahul A Sharma
    Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, ON, Canada.
  • Peng Yan
    Department of Interventional Neuroradiology, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Room 603, No. 6 Tiantan Xili, Dongcheng District, Beijing, China.
  • Parnian Arjmand

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