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Performance of Chatgpt in ophthalmology exam; human versus AI
Ali Safa Balci1,2, Zeliha Yazar3, Banu Turgut Ozturk4
1Department of Ophthalmology, Beyoglu Eye Training and Research Hospital, University of Health Sciences, 34420, Istanbul, Turkey. alisafabalci@gmail.com.
Purpose:
This cross-sectional study focuses on evaluating the success rate of ChatGPT in answering questions from the 'Resident Training Development Exam' and comparing these results with the performance of the ophthalmology residents.
Methods:
The 75 exam questions, across nine sections and three difficulty levels, were presented to ChatGPT. The responses and explanations were recorded. The readability and complexity of the explanations were analyzed and The Flesch Reading Ease (FRE) score (0-100) was recorded using the program named Readable. Residents were categorized into four groups based on their seniority. The overall and seniority-specific success rates of the residents were compared separately with ChatGPT.
Results:
Out of 69 questions, ChatGPT answered 37 correctly (53.62%). The highest success was in Lens and Cataract (77.77%), and the lowest in Pediatric Ophthalmology and Strabismus (0.00%). Of 789 residents, overall accuracy was 50.37%. Seniority-specific accuracy rates were 43.49%, 51.30%, 54.91%, and 60.05% for 1st to 4th-year residents. ChatGPT ranked 292nd among residents. Difficulty-wise, 11 questions were easy, 44 moderate, and 14 difficult. ChatGPT's accuracy for each level was 63.63%, 54.54%, and 42.85%, respectively. The average FRE score of responses generated by ChatGPT was found to be 27.56 ± 12.40.
Conclusion:
ChatGPT correctly answered 53.6% of questions in an exam for residents. ChatGPT has a lower success rate on average than a 3rd year resident. The readability of responses provided by ChatGPT is low, and they are difficult to understand. As difficulty increases, ChatGPT's success decreases. Predictably, these results will change with more information loaded into ChatGPT.

