ReviewCureus2024
Potential of ChatGPT to Pass the Japanese Medical and Healthcare Professional National Licenses: A Literature Review.
Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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
10 citing papers in PubMed.
- Performance Evaluation of Large Language Models in Multilingual Medical Multiple-Choice Questions: Mixed Methods Study.JMIR medical education · 2026Article
- Large Language Models as Simulated Candidates in Objective Structured Clinical Examinations: A Rubric-Mapping Proof-of-Concept Study.Advances in medical education and practice · 2026Article
- ChatGPT in Medical Education: Bibliometric and Visual Analysis.JMIR medical education · 2025Review
- Performance of artificial intelligence chatbots in National dental licensing examination.Journal of dental sciences · 2025Article
- Factors Associated with Lower Performance of Artificial Intelligence on Answering Undergraduate Medical Education Multiple-Choice Questions.Medical science educator · 2025Article
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- ChatGPT (GPT-4V) Performance on the Healthcare Information Technologist Examination in Japan.Cureus · 2025Article
- Sentiment analysis of social media responses to the approval of lecanemab for the treatment of Alzheimer's disease in Japan.Journal of Alzheimer's disease reportsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This systematic review aimed to assess the academic potential of ChatGPT (GPT-3.5, 4, and 4V) for Japanese national medical and healthcare licensing examinations, taking into account its strengths and limitations. Electronic databases such as PubMed/Medline, Google Scholar, and ICHUSHI (a Japanese medical article database) were systematically searched for relevant articles, particularly those published between January 1, 2022, and April 30, 2024. A formal narrative analysis was conducted by systematically arranging similarities and differences between individual research findings together. After rigorous screening, we reviewed 22 articles. Except for one article, all articles that evaluated GPT-4 showed that this tool could pass each exam containing text only. However, some studies also reported that, despite the possibility to pass, the results of GPT-4 were worse than those of the actual examinee. Moreover, the newest model GPT-4V insufficiently recognized images, thereby providing insufficient answers to questions that involved images and figures/tables. Therefore, their precision needs to be improved to obtain better results.
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.