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TRUVACE RECORD VERSION
record: TRV-2026-2852
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:35:06.514889Z
status: published
lens: p_space
sector: health
headline: Performance of ChatGPT in medical examinations: A systematic review and a meta‐analysis
dek: The use of ChatGPT, an artificial intelligence (AI) language model, has been described in various scientific and medical applications.1 With its human-like conversation capacity and large quantity of data, ChatGPT has the potential to become an important medical education tool.2 ChatGPT's performance in different medical knowledge examinations has been recently studied in various medical disciplines. However, reported rates of correct answers vary dramatically across different examinations and medical fields.3,…
gain_title: (none)
problem_title: A meta-analysis of 19 studies found ChatGPT 3.5 answered a mean 61.1% of medical multiple-choice exam questions correctly, roughly a passing grade and well below the 95% the authors say a reliable educational tool would need.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: A meta-analysis of 19 studies found ChatGPT 3.5 answered a mean 61.1% of medical multiple-choice exam questions correctly, roughly a passing grade and well below the 95% the authors say a reliable educational tool would need.
problem_evidence: The mean performance of ChatGPT was 61.1% (95% CI 56.1%–66.0% | A correct response rate of more than 95% may allow ChatGPT to become a reliable educational tool
quick_read: A systematic review and meta-analysis of 19 peer-reviewed studies found that ChatGPT version 3.5 answered a mean 61.1% of multiple-choice questions correctly across medical examinations (95% CI 56.1%–66.0%). The authors describe this as approximately a passing grade.

Scores varied widely, from 40% on a biomedical admission test to 100% on a diabetes knowledge questionnaire. The authors say this makes ChatGPT's use for exam preparation something to approach with caution, since medical education and test preparation form a large industrial market.

They say a correct response rate above 95% might make ChatGPT a reliable educational tool, and that it is unknown whether future versions will reach that level because the training data was not built with medical education in mind.
limitation: The review included only studies of ChatGPT version 3.5, the included studies were heterogeneous with the number of answer choices per exam unreported, and the authors say tool performance may be overestimated.
tag: Evidence-backed problem
key_points: Searches of PubMed, Scopus and Web of Science ran up to 2 June 2023 and yielded 19 included articles. | Only peer-reviewed studies of English-language multiple-choice questions using ChatGPT version 3.5 were included. | Plastic surgery, the United States Medical Licensing Examinations and anaesthesia each accounted for two studies (11% each). | The median exam had 242 questions, ranging from 20 in medical physiology to 3705 in anaesthesia. | Pooled ChatGPT accuracy was 61.1%, with individual exams ranging from 40% to 100%. | The authors advise that preparing for exams with ChatGPT should be done with proper caution.
rundown: Two reviewers (RM and GL) screened titles and abstracts independently, with a third reviewer (YB) resolving disagreements. Studies were excluded if they tested non-English prompts, formats other than multiple-choice such as open questions or frequently asked questions, or versions other than 3.5.

From each study the team extracted the medical field, number of questions, number correct and a 95% confidence interval for the performance rate, then analysed the data with MedCalc and OpenMeta[Analyst]. Question counts averaged 524.5 with a standard deviation of 847.2.

The authors conclude ChatGPT correctly answered the majority of questions but only at around a passing level. They suggest future meta-analyses should cover newer chatbot versions to update the picture for medical education.
sources:
- peer_reviewed | BJOG: An International Journal of Obstetrics & Gynaecology | https://doi.org/10.1111/1471-0528.17641 | 2023-08-21
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