Evidence map›Paper›PMID 40352979›Full record

ArticleMedical science educator2025

Can ChatGPT-4o Really Pass Medical Science Exams? A Pragmatic Analysis Using Novel Questions.

Philip M Newton, Christopher J Summers, Uzman Zaheer, Maira Xiromeriti, Jemima R Stokes, Jaskaran Singh Bhangu, Elis G Roome, Alanna Roberts-Phillips, Darius Mazaheri-Asadi, Cameron D Jones and 8 more

Abstract read
In one paragraph

Article in Medical science educator, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Medical science educator · 2024
    Article
  9. Review
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Philip M NewtonSwansea University Medical School, Swansea, Wales, SA2 8PP UK.ORCID 0000-0002-5272-7979
Christopher J SummersSwansea University Medical School, Swansea, Wales, SA2 8PP UK.ORCID 0009-0000-5336-2492
Uzman ZaheerSwansea University Medical School, Swansea, Wales, SA2 8PP UK.ORCID 0009-0008-2148-1532
Maira XiromeritiSwansea University Medical School, Swansea, Wales, SA2 8PP UK.ORCID 0000-0002-2975-184X
Jemima R StokesSwansea University Medical School, Swansea, Wales, SA2 8PP UK.ORCID 0000-0003-2623-0245
Jaskaran Singh BhanguSwansea University Medical School, Swansea, Wales, SA2 8PP UK.
Elis G RoomeSwansea University Medical School, Swansea, Wales, SA2 8PP UK.ORCID 0009-0009-5845-4164
Alanna Roberts-PhillipsSwansea University Medical School, Swansea, Wales, SA2 8PP UK.
Darius Mazaheri-AsadiSwansea University Medical School, Swansea, Wales, SA2 8PP UK.ORCID 0009-0002-7999-3123
Cameron D JonesSwansea University Medical School, Swansea, Wales, SA2 8PP UK.
Stuart HughesSwansea University Medical School, Swansea, Wales, SA2 8PP UK.
Dominic GilbertSwansea University Medical School, Swansea, Wales, SA2 8PP UK.ORCID 0009-0002-0024-3662
Ewan JonesSwansea University Medical School, Swansea, Wales, SA2 8PP UK.ORCID 0009-0002-9221-1990
Keioni EssexSwansea University Medical School, Swansea, Wales, SA2 8PP UK.
Emily C EllisSwansea University Medical School, Swansea, Wales, SA2 8PP UK.ORCID 0009-0005-6493-9337
Ross DaveySwansea University Medical School, Swansea, Wales, SA2 8PP UK.ORCID 0000-0001-9852-1653
Adrienne A CoxSwansea University Medical School, Swansea, Wales, SA2 8PP UK.ORCID 0000-0002-3902-3491
Jessica A BassettSwansea University Medical School, Swansea, Wales, SA2 8PP UK.ORCID 0009-0002-2146-2987

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ChatGPT apparently shows excellent performance on high-level professional exams such as those involved in medical assessment and licensing. This has raised concerns that ChatGPT could be used for academic misconduct, especially in unproctored online exams. However, ChatGPT has previously shown weaker performance on questions with pictures, and there have been concerns that ChatGPT's performance may be artificially inflated by the public nature of the sample questions tested, meaning they likely formed part of the training materials for ChatGPT. This led to suggestions that cheating could be mitigated by using novel questions for every sitting of an exam and making extensive use of picture-based questions. These approaches remain untested. Here, we tested the performance of ChatGPT-4o on existing medical licensing exams in the UK and USA, and on novel questions based on those exams. ChatGPT-4o scored 94% on the United Kingdom Medical Licensing Exam Applied Knowledge Test and 89.9% on the United States Medical Licensing Exam Step 1. Performance was not diminished when the questions were rewritten into novel versions, or on completely novel questions which were not based on any existing questions. ChatGPT did show reduced performance on questions containing images when the answer options were added to an image as text labels. These data demonstrate that the performance of ChatGPT continues to improve and that secure testing environments are required for the valid assessment of both foundational and higher order learning. Supplementary Information: The online version contains supplementary material available at 10.1007/s40670-025-02293-z.

Indexed as

Academic integrityAssessment validityCheatingEvidence-based educationMCQsPragmatism

Identifiers

PMID40352979
PMCPMC12058600

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.