ArticleFrontiers in medicine2023
ChatGPT's performance in German OB/GYN exams - paving the way for AI-enhanced medical education and clinical practice.
Article in Frontiers in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.
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Who cites it
28 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Digital affordances of AI chatbots in nursing education: a systematic review of learning gains and gaps in the evidence.Frontiers in medicine · 2026Pooled 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
- An exploratory study of the use of artificial intelligence-based virtual patients to enhance dentist-patient communication training.BMC medical education · 2026Trial
- Humans vs. large language models in neurology board examination: performance, limitations, and reference reliability.Acta neurologica Belgica · 2026Article
- Large Language Models in German Continuing Medical Education Assessments: Protocol for a Fully Crossed Experimental Study.JMIR research protocols · 2026Article
- Discrepancy between medical knowledge and clinical reasoning: evaluating large language models in prenatal diagnosis.Frontiers in digital health · 2026Article
- Medical education in obstetrics and gynecology: A global update from 2025.Acta obstetricia et gynecologica Scandinavica · 2026Review
- Comparative performance of ChatGPT-5 and DeepSeek on the Chinese ultrasound medicine senior professional title examination.Frontiers in digital health · 2026Article
- Determining the reliability of Artificial Intelligence programs in medical faculty board exams.Pakistan journal of medical sciences · 2025Article
- Exploring the potential of AI-powered applications for clinical decision-making in gynecologic oncology.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2025Article
- Artificial Intelligence in Endodontic Education: A Systematic Review with Frequentist and Bayesian Meta-Analysis of Student-Based Evidence.Dentistry journal · 2025Review
- Applications, Challenges, and Prospects of Generative Artificial Intelligence Empowering Medical Education: Scoping Review.JMIR medical education · 2025Article
- Assessing the Role of Large Language Models Between ChatGPT and DeepSeek in Asthma Education for Bilingual Individuals: Comparative Study.JMIR medical informatics · 2025Article
- Automatic- and Transformer-Based Automatic Item Generation: A Critical Review.Journal of Intelligence · 2025Review
- Can ChatGPT Provide Patient-Friendly and Reliable Information on Cervical Cancer Screening? A Study of ChatGPT-Generated Information in Polish.Medical science monitor : international medical journal of experimental and clinical research · 2025Article
- AI-driven simplification of surgical reports in gynecologic oncology: A potential tool for patient education.Acta obstetricia et gynecologica Scandinavica · 2025Article
- Comparative analysis of ChatGPT 3.5 and ChatGPT 4 obstetric and gynecological knowledge.Scientific reports · 2025Article
- Automating Responses to Patient Portal Messages Using Generative AI.Applied clinical informatics · 2025Article
- Exploring medical students' intention to use of ChatGPT from a programming course: a grounded theory study in China.BMC medical education · 2025Article
- ChatGPT-4 Performance on German Continuing Medical Education-Friend or Foe (Trick or Treat)? Protocol for a Randomized Controlled Trial.JMIR research protocols · 2025Article
Corrections and comments
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Authors and funding
11 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Chat Generative Pre-Trained Transformer (ChatGPT) is an artificial learning and large language model tool developed by OpenAI in 2022. It utilizes deep learning algorithms to process natural language and generate responses, which renders it suitable for conversational interfaces. ChatGPT's potential to transform medical education and clinical practice is currently being explored, but its capabilities and limitations in this domain remain incompletely investigated. The present study aimed to assess ChatGPT's performance in medical knowledge competency for problem assessment in obstetrics and gynecology (OB/GYN). Methods: Two datasets were established for analysis: questions (1) from OB/GYN course exams at a German university hospital and (2) from the German medical state licensing exams. In order to assess ChatGPT's performance, questions were entered into the chat interface, and responses were documented. A quantitative analysis compared ChatGPT's accuracy with that of medical students for different levels of difficulty and types of questions. Additionally, a qualitative analysis assessed the quality of ChatGPT's responses regarding ease of understanding, conciseness, accuracy, completeness, and relevance. Non-obvious insights generated by ChatGPT were evaluated, and a density index of insights was established in order to quantify the tool's ability to provide students with relevant and concise medical knowledge. Results: ChatGPT demonstrated consistent and comparable performance across both datasets. It provided correct responses at a rate comparable with that of medical students, thereby indicating its ability to handle a diverse spectrum of questions ranging from general knowledge to complex clinical case presentations. The tool's accuracy was partly affected by question difficulty in the medical state exam dataset. Our qualitative assessment revealed that ChatGPT provided mostly accurate, complete, and relevant answers. ChatGPT additionally provided many non-obvious insights, especially in correctly answered questions, which indicates its potential for enhancing autonomous medical learning. Conclusion: ChatGPT has promise as a supplementary tool in medical education and clinical practice. Its ability to provide accurate and insightful responses showcases its adaptability to complex clinical scenarios. As AI technologies continue to evolve, ChatGPT and similar tools may contribute to more efficient and personalized learning experiences and assistance for health care providers.
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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.