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In-depth analysis of ChatGPT’s performance based on specific signaling words and phrases in the question stem of 2377 USMLE step 1 style questions
27
Zitationen
12
Autoren
2024
Jahr
Abstract
= -0.306; p < 0.001, maintaining comparable accuracy to the human user peer group across different levels of question difficulty. Notably, ChatGPT outperformed in serology-related questions (61.1% vs. 53.8%; p = 0.005) but struggled with ECG-related content (42.9% vs. 55.6%; p = 0.021). ChatGPT achieved statistically significant worse performances in pathophysiology-related question stems. (Signal phrase = "what is the most likely/probable cause"). ChatGPT performed consistent across various question categories and difficulty levels. These findings emphasize the need for further investigations to explore the potential and limitations of ChatGPT in medical examination and education.
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Autoren
Institutionen
- Freie Universität Berlin(DE)
- Charité - Universitätsmedizin Berlin(DE)
- Humboldt-Universität zu Berlin(DE)
- Klinikum rechts der Isar(DE)
- Harvard University(US)
- Technical University of Munich(DE)
- Brigham and Women's Hospital(US)
- University Hospital Regensburg(DE)
- Erasmus University Rotterdam(NL)
- Queen Mary University of London(GB)
- Guangdong Provincial People's Hospital(CN)
- Emory University(US)
- Munich Business School(DE)
- Ludwig-Maximilians-Universität München(DE)
- Instituto Ivo Pitanguy(BR)