Publication | Open Access
Performance of ChatGPT on USMLE: Potential for AI-Assisted Medical Education Using Large Language Models
615
Citations
13
References
2022
Year
Unknown Venue
Artificial IntelligenceChatbotEngineeringClinical Decision-makingLarge Language ModelNatural Language ProcessingLarge Language ModelsComputational LinguisticsAi HealthcareMachine TranslationLinguisticsOutcomes ResearchClinical Decision SupportComputer ScienceMedical Decision AnalysisAi EducationLlm-based AgentPatient SafetyContinuing Medical EducationPatient EducationMedicineClinical Decision Support SystemHealth Informatics
ABSTRACT We evaluated the performance of a large language model called ChatGPT on the United States Medical Licensing Exam (USMLE), which consists of three exams: Step 1, Step 2CK, and Step 3. ChatGPT performed at or near the passing threshold for all three exams without any specialized training or reinforcement. Additionally, ChatGPT demonstrated a high level of concordance and insight in its explanations. These results suggest that large language models may have the potential to assist with medical education, and potentially, clinical decision-making.
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