ArticleCureus2023
ChatGPT Conquers the Saudi Medical Licensing Exam: Exploring the Accuracy of Artificial Intelligence in Medical Knowledge Assessment and Implications for Modern Medical Education.
Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 5 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 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
- Performance of large language models in medical licensing examinations: a systematic review and meta-analysis.Journal of educational evaluation for health professions · 2025Pooled 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
- Performance of ChatGPT Across Different Versions in Medical Licensing Examinations Worldwide: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2024Pooled it
- Pooled it
- Stepwise Diagnostic Evaluation of Chinese Large Language Models: Comparative Study of Common and Rare Diseases.Journal of medical Internet research · 2026Article
- LLMs in Medical Education for Autism Caregivers: A Comparative Evaluation of Accuracy, Readability, Actionability, and Neurodiversity-Affirming Language.Healthcare (Basel, Switzerland) · 2026Article
- Textbook-level medical knowledge in large language models: comparative evaluation using Japanese National Medical Examination.BMC medical informatics and decision making · 2026Article
- Enhancing Knowledge Integration and Self-Directed Learning in Undergraduate Medical Education Through an AI-Based Multimodal Platform.Advances in medical education and practice · 2026Article
- Evaluating large language models as graders of medical short answer questions: a comparative analysis with expert human graders.Medical education online · 2025Article
- Review
- Assessing ChatGPT responses to patient questions on epidural steroid injections: A comparative study of general vs specific queries.Interventional pain medicine · 2025Article
- Performance of ChatGPT-4 on Taiwanese Traditional Chinese Medicine Licensing Examinations: Cross-Sectional Study.JMIR medical education · 2025Article
- ChatGPT and Other Large Language Models in Medical Education - Scoping Literature Review.Medical science educator · 2025Review
- Supporting postgraduate exam preparation with large language models: implications for traditional Chinese medicine education.Frontiers in medicine · 2025Article
- Accuracy and reliability of Manus, ChatGPT, and Claude in case-based dental diagnosis.Frontiers in oral health · 2025Article
- Advancing medical AI: GPT-4 and GPT-4o surpass GPT-3.5 in Taiwanese medical licensing exams.PloS one · 2025Article
- Review
- Evaluating AI Competence in Specialized Medicine: Comparative Analysis of ChatGPT and Neurologists in a Neurology Specialist Examination in Spain.JMIR medical education · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background The application of artificial intelligence (AI) in education is undergoing rapid advancements, with models such as ChatGPT-4 showing potential in medical education. This study aims to evaluate the proficiency of ChatGPT-4 in answering Saudi Medical Licensing Exam (SMLE) questions. Methodology A dataset of 220 questions across four medical disciplines was used. The model was trained using a specific code to answer the questions accurately, and its performance was assessed using key performance indicators, difficulty level, and exam sections. Results ChatGPT-4 demonstrated an overall accuracy of 88.6%. It showed high proficiency with
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.