Computer Vision Meets Large Language Models: Performance of ChatGPT 4.0 on Dermatology Boards-Style Practice Questions

Background: ChatGPT is a generative artificial intelligence that has numerous professional applications. Applications in medical education are currently being explored. ChatGPT 4.0 performance on image-based dermatology boards-style practice questions has not been assessed. Objective: The objective of this study was to determine the accuracy with which ChatGPT can answer dermatology boards examination practice questions. Methods: 150 multiple-choice questions from the popular question bank DermQbank were inputted into ChatGPT. Of these, 83 were text-only questions and 67 had associated images. These same questions were inputted into ChatGPT again in July 2024. An additional 150 questions were inputted for a total of 300 different questions where 169 were text-only and 133 had associated images. Results: Of the aggregate 300 question data, ChatGPT answered 232 questions correctly (77.3%). ChatGPT performed significantly better with text-only questions than with questions that included images (85.2% (144/169) vs 67.7% (90/133), P<.001). Of image-based questions, ChatGPT performed better with clinical image questions than with dermatopathology questions (69.0% (78/133) vs. 58.8% (10/17), P=.40), but this difference was not statistically significant partially due to the sample size of the dermatopathology questions. Compared to post-graduate year 4 (PGY-4) residents, ChatGPT performed above the 46th percentile. ChatGPT agreed with the answer choice picked by the majority of question bank users 75.3% of the time. Multivariable regression demonstrated that significant predictive variables for ChatGPT answering a question correctly included the percent of dermatology trainees who answered a question correctly and whether the question was text-based (P<.001and P=.004, respectively). Conclusions: ChatGPT answered 77.3% of dermatology board examination practice questions correctly, performing above the 46th percentile of PGY-4 question bank users. If using ChatGPT as a study resource for dermatology board examination preparation, residents should be judicious with exactly how they employ ChatGPT to avoid learning incorrect information.

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Publication Details

Journal
SKIN The Journal of Cutaneous Medicine
Published
2024-09-15
DOI
https://doi.org/10.25251/skin.8.5.5
Citations
5
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.60
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article

Computer Vision Meets Large Language Models: Performance of ChatGPT 4.0 on Dermatology Boards-Style Practice Questions

Leigh Hatch, Karim Hanna, R M Hanna, Logan R. Smith
5 citations
SKIN The Journal of Cutaneous Medicine
Artificial Intelligence in Healthcare and Education
0.60
article

Computer Vision Meets Large Language Models: Performance of ChatGPT 4.0 on Dermatology Boards-Style Practice Questions

Leigh Hatch, Karim Hanna, R M Hanna, Logan R. Smith
article en
5 citations

Abstract

Background: ChatGPT is a generative artificial intelligence that has numerous professional applications. Applications in medical education are currently being explored. ChatGPT 4.0 performance on image-based dermatology boards-style practice questions has not been assessed. Objective: The objective of this study was to determine the accuracy with which ChatGPT can answer dermatology boards examination practice questions. Methods: 150 multiple-choice questions from the popular question bank DermQbank were inputted into ChatGPT. Of these, 83 were text-only questions and 67 had associated images. These same questions were inputted into ChatGPT again in July 2024. An additional 150 questions were inputted for a total of 300 different questions where 169 were text-only and 133 had associated images. Results: Of the aggregate 300 question data, ChatGPT answered 232 questions correctly (77.3%). ChatGPT performed significantly better with text-only questions than with questions that included images (85.2% (144/169) vs 67.7% (90/133), P<.001). Of image-based questions, ChatGPT performed better with clinical image questions than with dermatopathology questions (69.0% (78/133) vs. 58.8% (10/17), P=.40), but this difference was not statistically significant partially due to the sample size of the dermatopathology questions. Compared to post-graduate year 4 (PGY-4) residents, ChatGPT performed above the 46th percentile. ChatGPT agreed with the answer choice picked by the majority of question bank users 75.3% of the time. Multivariable regression demonstrated that significant predictive variables for ChatGPT answering a question correctly included the percent of dermatology trainees who answered a question correctly and whether the question was text-based (P<.001and P=.004, respectively). Conclusions: ChatGPT answered 77.3% of dermatology board examination practice questions correctly, performing above the 46th percentile of PGY-4 question bank users. If using ChatGPT as a study resource for dermatology board examination preparation, residents should be judicious with exactly how they employ ChatGPT to avoid learning incorrect information.

SKIN The Journal of Cutaneous MedicineVol. 8(5)
Openalex Percentile: Top 29%
Artificial Intelligence in Healthcare and Education
0.60
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