Litcius/Paper detail

Comparing ChatGPT and GPT-4 performance in USMLE soft skill assessments

Dana Brin, Vera Sorin, Akhil Vaid, Ali Soroush, Benjamin S. Glicksberg, Alexander W. Charney, Girish N. Nadkarni, Eyal Klang

2023Scientific Reports322 citationsDOIOpen Access PDF

Abstract

The United States Medical Licensing Examination (USMLE) has been a subject of performance study for artificial intelligence (AI) models. However, their performance on questions involving USMLE soft skills remains unexplored. This study aimed to evaluate ChatGPT and GPT-4 on USMLE questions involving communication skills, ethics, empathy, and professionalism. We used 80 USMLE-style questions involving soft skills, taken from the USMLE website and the AMBOSS question bank. A follow-up query was used to assess the models' consistency. The performance of the AI models was compared to that of previous AMBOSS users. GPT-4 outperformed ChatGPT, correctly answering 90% compared to ChatGPT's 62.5%. GPT-4 showed more confidence, not revising any responses, while ChatGPT modified its original answers 82.5% of the time. The performance of GPT-4 was higher than that of AMBOSS's past users. Both AI models, notably GPT-4, showed capacity for empathy, indicating AI's potential to meet the complex interpersonal, ethical, and professional demands intrinsic to the practice of medicine.

Topics & Concepts

EmpathyConsistency (knowledge bases)Soft skillsInterpersonal communicationUnited States Medical Licensing ExaminationMedical educationPsychologyComputer scienceArtificial intelligenceMedicineMedical schoolSocial psychologyArtificial Intelligence in Healthcare and EducationClinical Reasoning and Diagnostic SkillsEthics in Clinical Research