Evidence map›Paper›PMID 37865883›Full record

ReviewJournal of medical Internet research2023

A SWOT (Strengths, Weaknesses, Opportunities, and Threats) Analysis of ChatGPT in the Medical Literature: Concise Review.

Daniel Gödde, Sophia Nöhl, Carina Wolf, Yannick Rupert, Lukas Rimkus, Jan Ehlers, Frank Breuckmann, Timur Sellmann

Abstract readReview
In one paragraph

Review in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 2 pooled it
–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

30 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  5. Review
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  7. Article
  8. Article
  9. Article
  10. Use of AI in Family Medicine Publications: A Joint Editorial from Journal Editors.Journal of the American Board of Family Medicine : JABFM · 2025
    Article
  11. Article
  12. Article
  13. Prospects and perils of ChatGPT in diabetes.World journal of diabetes · 2025
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
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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

8 authors.

Daniel GöddeDepartment of Pathology and Molecularpathology, Helios University Hospital Wuppertal, Witten/Herdecke University, Witten, Germany.ORCID 0000-0002-8430-1411
Sophia NöhlFaculty of Health, Witten/Herdecke University, Witten, Germany.ORCID 0009-0008-7515-8300
Carina WolfFaculty of Health, Witten/Herdecke University, Witten, Germany.ORCID 0009-0003-0303-2825
Yannick RupertFaculty of Health, Witten/Herdecke University, Witten, Germany.ORCID 0009-0005-7430-2460
Lukas RimkusFaculty of Health, Witten/Herdecke University, Witten, Germany.ORCID 0009-0009-4468-7768
Jan EhlersDepartment of Didactics and Education Research in the Health Sector, Faculty of Health, Witten/Herdecke University, Witten, Germany.ORCID 0000-0001-6306-4173
Frank BreuckmannDepartment of Cardiology and Vascular Medicine, West German Heart and Vascular Center Essen, University Duisburg-Essen, Essen, Germany.ORCID 0000-0001-7245-8000
Timur SellmannDepartment of Anaesthesiology I, Witten/Herdecke University, Witten, Germany.ORCID 0000-0002-1471-6806

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChatGPT is a 175-billion-parameter natural language processing model that is already involved in scientific content and publications. Its influence ranges from providing quick access to information on medical topics, assisting in generating medical and scientific articles and papers, performing medical data analyses, and even interpreting complex data sets.

objectiveThe future role of ChatGPT remains uncertain and a matter of debate already shortly after its release. This review aimed to analyze the role of ChatGPT in the medical literature during the first 3 months after its release.

methodsWe performed a concise review of literature published in PubMed from December 1, 2022, to March 31, 2023. To find all publications related to ChatGPT or considering ChatGPT, the search term was kept simple ("ChatGPT" in AllFields). All publications available as full text in German or English were included. All accessible publications were evaluated according to specifications by the author team (eg, impact factor, publication modus, article type, publication speed, and type of ChatGPT integration or content). The conclusions of the articles were used for later SWOT (strengths, weaknesses, opportunities, and threats) analysis. All data were analyzed on a descriptive basis.

resultsOf 178 studies in total, 160 met the inclusion criteria and were evaluated. The average impact factor was 4.423 (range 0-96.216), and the average publication speed was 16 (range 0-83) days. Among the articles, there were 77 editorials (48,1%), 43 essays (26.9%), 21 studies (13.1%), 6 reviews (3.8%), 6 case reports (3.8%), 6 news (3.8%), and 1 meta-analysis (0.6%). Of those, 54.4% (n=87) were published as open access, with 5% (n=8) provided on preprint servers. Over 400 quotes with information on strengths, weaknesses, opportunities, and threats were detected. By far, most (n=142, 34.8%) were related to weaknesses. ChatGPT excels in its ability to express ideas clearly and formulate general contexts comprehensibly. It performs so well that even experts in the field have difficulty identifying abstracts generated by ChatGPT. However, the time-limited scope and the need for corrections by experts were mentioned as weaknesses and threats of ChatGPT. Opportunities include assistance in formulating medical issues for nonnative English speakers, as well as the possibility of timely participation in the development of such artificial intelligence tools since it is in its early stages and can therefore still be influenced.

conclusionsArtificial intelligence tools such as ChatGPT are already part of the medical publishing landscape. Despite their apparent opportunities, policies and guidelines must be implemented to ensure benefits in education, clinical practice, and research and protect against threats such as scientific misconduct, plagiarism, and inaccuracy.

Indexed as

Artificial IntelligenceData AnalysisEducational StatusHumansLanguageNatural Language Processingartificial intelligencechatbotchatbotsChatGPTconcise revieweducation technologymachine learningmedical educationreview methodologyreview methodsSWOT

Identifiers

PMID37865883
PMCPMC10690535

What Socratic 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 Socratic graph.