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ChatGPT in Ophthalmology: Past, Present, and Future.

Amit Toledano1, Ehud Raz Gatt2, Asaf Laks1

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Newer AI models, ChatGPT-4o and ChatGPT-5, show improved diagnostic accuracy in ophthalmology cases compared to older versions and approach human clinician performance.

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Area of Science:

  • Ophthalmology
  • Artificial Intelligence
  • Medical Diagnostics

Background:

  • Large language models (LLMs) are rapidly evolving.
  • Benchmarking LLMs in ophthalmology is needed to assess clinical utility.
  • Comparing newer LLMs to earlier versions and human experts is crucial.

Purpose of the Study:

  • To evaluate the diagnostic accuracy of ChatGPT-4o and ChatGPT-5 for ophthalmic conditions.
  • To compare the performance of these newer AI models against ChatGPT-3.5, residents, and specialists.

Main Methods:

  • Retrospective cohort study at an academic tertiary medical center.
  • Reviewed 63 ophthalmology patient cases from June 2022 to January 2023.
  • Created two diagnostic scenarios per patient: history alone (Hx) and history with examination (Hx and Ex).
  • Assessed diagnostic accuracy of ChatGPT-4o and ChatGPT-5 for each scenario.

Main Results:

  • Using history alone, ChatGPT-5 (73%) and ChatGPT-4o (70%) outperformed ChatGPT-3.5 (54%) and neared resident (75%) and attending (71%) accuracy.
  • With examination findings, ChatGPT-5 (94%) and ChatGPT-4o (89%) significantly surpassed ChatGPT-3.5 (68%).
  • The latest AI models matched or exceeded human diagnostic performance (residents 94%, attendings 87%).

Conclusions:

  • ChatGPT-4o and ChatGPT-5 demonstrate significantly improved diagnostic capabilities in ophthalmology compared to ChatGPT-3.5.
  • These advanced AI models achieve diagnostic accuracy comparable to or exceeding that of human clinicians in ophthalmic case diagnosis.