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Evaluating the Artificial Intelligence Performance Growth in Ophthalmic Knowledge.

Cheng Jiao1, Neel R Edupuganti1, Parth A Patel2

  • 1Ophthalmology, Augusta University Medical College of Georgia, Augusta, USA.

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|October 23, 2023
PubMed
Summary
This summary is machine-generated.

Chat Generative Pre-Trained Transformer (ChatGPT)-4.0 significantly outperforms ChatGPT-3.5 in ophthalmic case challenges, demonstrating superior accuracy, especially in neuro-ophthalmology and image-related questions. This highlights the potential of advanced AI in ophthalmology diagnostics and education.

Keywords:
artificial intelligencechatgptmedical educationnatural language processing modelsophthalmology

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Area of Science:

  • Ophthalmology
  • Artificial Intelligence
  • Medical Diagnostics

Background:

  • Large language models (LLMs) like ChatGPT are increasingly used in medicine.
  • Evaluating the diagnostic capabilities of different LLM versions is crucial for their application.
  • Ophthalmic case challenges require accurate interpretation of clinical data and images.

Purpose of the Study:

  • To compare the performance of ChatGPT-3.5 and ChatGPT-4.0 in solving multiple-choice ophthalmic case challenges.
  • To analyze performance across ophthalmology subspecialties, question difficulty, and image-based questions.
  • To assess response conciseness and alignment with expert human responses.

Main Methods:

  • Multiple-choice ophthalmic case questions from the American Academy of Ophthalmology (AAO) 'Diagnosis This' were used.
  • Accuracy of ChatGPT-3.5 and ChatGPT-4.0 was compared.
  • Statistical analyses included chi-squared test, Fisher's exact test, Student's t-test, and ANOVA (p<0.05 significance).

Main Results:

  • ChatGPT-4.0 achieved significantly higher accuracy (75%) than ChatGPT-3.5 (46%, p<0.01).
  • ChatGPT-4.0 showed marked improvement in neuro-ophthalmology (100% vs. 38%, p=0.03) and image-related questions (73% vs. 46%, p=0.07).
  • ChatGPT-4.0 provided more concise answers and better aligned with AAO respondents' answers (57.3% vs. 41.4%, p<0.01).

Conclusions:

  • ChatGPT-4.0 significantly outperforms ChatGPT-3.5 in ophthalmic case challenges.
  • The advanced AI model shows promise for improving ophthalmic diagnostics and medical education.
  • Further research into AI applications in specialized medical fields is warranted.