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Cited by 55Academic Writing and PublishingAcademic integrity and plagiarismArtificial Intelligence in Healthcare and Education

The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.

A review of top cardiology and cardiovascular medicine journal guidelines regarding the use of generative artificial intelligence tools in scientific writing

Open access
Inam, Maha, Sheikh, Sana, Minhas, Abdul Mannan Khan, Vaughan, Elizabeth M., Krittanawong, Chayakrit, Samad, Zainab, Lavie, Carl J., Khoja, Adeel, D'Cruze, Melaine, Slipczuk, Leandro, Alarakhiya, Farhana, Naseem, Azra, Haider, Adil H., Virani, Salim S.·2024·Current Problems in Cardiology
DOI 10.1016/j.cpcardiol.2024.102387
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Abstract

BACKGROUND Generative Artificial Intelligence (AI) tools have experienced rapid development over the last decade and are gaining increasing popularity as assistive models in academic writing. However, the ability of AI to generate reliable and accurate research articles is a topic of debate. Major scientific journals have issued policies regarding the contribution of AI tools in scientific writing. METHODS We conducted a review of the author and peer reviewer guidelines of the top 25 Cardiology and Cardiovascular Medicine journals as per the 2023 SCImago rankings. Data were obtained though reviewing journal websites and directly emailing the editorial office. Descriptive data regarding journal characteristics were coded on SPSS. Subgroup analyses of the journal guidelines were conducted based on the publishing company policies. RESULTS Our analysis revealed that all scientific journals in our study permitted the documented use of AI in scientific writing with certain limitations as per ICMJE recommendations. We found that AI tools cannot be included in the authorship or be used for image generation, and that all authors are required to assume full responsibility of their submitted and published work. The use of generative AI tools in the peer review process is strictly prohibited. CONCLUSION Guidelines regarding the use of generative AI in scientific writing are standardized, detailed, and unanimously followed by all journals in our study according to the recommendations set forth by international forums. It is imperative to ensure that these policies are carefully followed and updated to maintain scientific integrity.

Overview

Integrity signals

Registry

Crossref · 10.1016/j.cpcardiol.2024.102387

Cites

30 of 30 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Citations

Cites

Research works printed but not linked: 3

  1. 2023, J Rank Cardiol Cardiovasc Med
  2. 2023, Artif Intell Authorship
  3. Science funding agencies say no to using AI for peer review [Internet]. [cited 2023 Oct 16]. Available from: https://www.science.org/content/article/science-funding-agencies-say-no-using-ai-peer-review.

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Metadata

Authors
Inam, M., Sheikh, S., Minhas, A. M. K., Vaughan, E. M., Krittanawong, C., Samad, Z., Lavie, C. J., Khoja, A., D'Cruze, M., Slipczuk, L., Alarakhiya, F., Naseem, A., Haider, A. H., & Virani, S. S.
Affiliations
  • Aga Khan University (PK)
  • Baylor College of Medicine (US)
  • NYU Langone Health (US)
  • The University of Queensland (AU)
  • Aga Khan University Hospital (PK)
  • Albert Einstein College of Medicine (US)
  • Aga Khan University Nairobi (KE)
Corresponding author
Virani, Salim S.
ORCID
Venue
Current Problems in Cardiology
Publisher
Elsevier BV
Published
2024-03
Volume
49
Issue
3
Pages
102387
ISSN
0146-2806 (ISSN-L)
DOI
10.1016/j.cpcardiol.2024.102387
OpenAlex
W4390613603
Semantic Scholar
4d75bc6d1d751883abfceffba32cd8b5d4a03ade
Cited by
55
References
30
Citations by year
2026: 16 · 2025: 20 · 2024: 19
FWCI
5.91
Type
journal article
Language
en
Open access
Licence
Locations
  • Current Problems in Cardiology (publishedVersion)
  • PubMed (publishedVersion)
  • eCommons - AKU (Aga Khan University) (submittedVersion, cc-by-nc-nd)
Funders
National Institute of Diabetes and Digestive and Kidney Diseases (R01DK129474)
Topics
  • Social Sciences › Library and Information Sciences › Academic Writing and Publishing
  • Social Sciences › Education › Academic integrity and plagiarism
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
generative AI, AI in scientific writing, journal author guidelines, peer review policy, authorship, image generation, ICMJE recommendations, scientific integrity, cardiology journals
MeSH terms
Artificial Intelligence, Cardiology, Humans, Publishing, Writing, Editorial Policies

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.