Meta-research on reporting guidelines for artificial intelligence: are authors and reviewers encouraged enough in radiology, nuclear medicine, and medical imaging journals?
Open accessAbstract
PURPOSE: To determine how radiology, nuclear medicine, and medical imaging journals encourage and mandate the use of reporting guidelines for artificial intelligence (AI) in their author and reviewer instructions. METHODS: The primary source of journal information and associated citation data used was the Journal Citation Reports (June 2023 release for 2022 citation data; Clarivate Analytics, UK). The first- and second-quartile journals indexed in the Science Citation Index Expanded and the Emerging Sources Citation Index were included. The author and reviewer instructions were evaluated by two independent readers, followed by an additional reader for consensus, with the assistance of automatic annotation. Encouragement and submission requirements were systematically analyzed. The reporting guidelines were grouped as AI-specific, related to modeling, and unrelated to modeling. RESULTS: < 0.05 for all). CONCLUSION: The findings indicate that AI-specific guidelines are not commonly encouraged and mandated (i.e., requiring a filled-out checklist) by these journals, compared with guidelines related to modeling and unrelated to modeling, leaving vast space for improvement. This meta-research study hopes to contribute to the awareness of the imaging community for AI reporting guidelines and ignite large-scale group efforts by all stakeholders, making AI research less wasteful. CLINICAL SIGNIFICANCE: This meta-research highlights the need for improved encouragement of AI-specific guidelines in radiology, nuclear medicine, and medical imaging journals. This can potentially foster greater awareness among the AI community and motivate various stakeholders to collaborate to promote more efficient and responsible AI research reporting practices.
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Flagged first, then by citations
Cited by
Sorted by citations
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Rodríguez‐Hernández, A. G. (2025) · SAP Artificial Intelligence in Dentistry · doi:10.62486/aid202542
- Authors
- Koçak, B., Keleş, A., & Köse, F.
- Affiliations
- Sağlık Bilimleri Üniversitesi (TR)
- Corresponding author
- Koçak, Burak
- Venue
- Diagnostic and Interventional Radiology
- Publisher
- Galenos Yayinevi
- Published
- 2024-02-20
- Volume
- 0
- Issue
- 0
- Pages
- 0-0
- ISSN
- 1300-4360 (ISSN-L)
- 1305-3825
- 1305-3612
- PMC
- PMC11590734
- OpenAlex
- W4391980793
- Cited by
- 12
- References
- 74
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 4
- FWCI
- 1.12
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by-nc
- Locations
- Diagnostic and Interventional Radiology (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Academic Writing and Publishing
- Keywords
- artificial intelligence, reporting guidelines, author guidelines, journal editorial policy, radiology journals, research reporting practices
- MeSH terms
- Artificial Intelligence, Authorship, Diagnostic Imaging, Humans, Nuclear Medicine, Periodicals as Topic, Radiology, Guidelines as Topic
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