ArticleScientific reports2023
Comparing ChatGPT and GPT-4 performance in USMLE soft skill assessments.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 143 papers, 5 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
143 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Evaluating the Potential and Accuracy of ChatGPT-3.5 and 4.0 in Medical Licensing and In-Training Examinations: Systematic Review and Meta-Analysis.JMIR medical education · 2025Pooled it
- Accuracy of Large Language Models When Answering Clinical Research Questions: Systematic Review and Network Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Large Language Models and Empathy: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Performance of ChatGPT-3.5 and GPT-4 in national licensing examinations for medicine, pharmacy, dentistry, and nursing: a systematic review and meta-analysis.BMC medical education · 2024Pooled it
- Large language models for generating medical examinations: systematic review.BMC medical education · 2024Pooled it
- Patient-Representing Population's Perceptions of GPT-Generated Versus Standard Emergency Department Discharge Instructions: Randomized Blind Survey Assessment.Journal of medical Internet research · 2024Trial
- Can ChatGPT pass the polish national medical specialization examination in orthopedics and traumatology?Archives of orthopaedic and trauma surgery · 2026Article
- Artificial intelligence performance in the emergency medicine subspecialty examination conducted in Türkiye.Medicine · 2026Article
- Performance of GPT-4o and Claude in Medical Ethics Scenarios: Comparative Study.JMIR medical education · 2026Article
- Structured reasoning failures compromise LLM interpretation of clinical oncology notes.NPJ digital medicine · 2026Article
- Comparison of large language models and conventional machine learning in postoperative outcome prediction: a retrospective, multi-national development and validation study.Korean journal of anesthesiology · 2026Article
- A Multiassessment and Multiprofessional Agents Approach for Medical Chatbot Risk Estimation: Development and Evaluation Study.JMIR medical informatics · 2026Article
- Evaluation of large language models in cardiovascular surgery: a comparative study of board-level clinical question answering and generation.Journal of cardiothoracic surgery · 2026Article
- Evaluation Large Language Models' Time Dependent Consistency in Aesthetic Surgery Consultations and Comparison of Their Performance Across Different Clinical Domains.Aesthetic plastic surgery · 2026Article
- Comparative Evaluation of Deep-Reasoning Large Language Models for Ophthalmic Emergencies.Ophthalmology science · 2026Article
- Evaluation of GPT-5 in Periodontitis Staging and Grading: Retrospective Observational Study.JMIR formative research · 2026Observational
- Evaluating ChatGPT's Adherence to Medical Ethics: A Prerequisite for Artificial Intelligence in Medicine.Health care science · 2026Article
- ChatGPT in precision medicine.APL bioengineering · 2026Review
- An Exploratory Evaluation of GPT-5 in Periodontitis Staging and Grading Using Published Clinical Cases.Research square · 2026Article
- Development and validation of a deep learning-based emergency triage model: a feasibility and effectiveness study.BMC emergency medicine · 2026Article
83 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
8 authors.
Funding
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.