Evaluating Dental AI Research Papers: Key Considerations for Editors and Reviewers

Authors

• Sergio E. Uribe, Riga Stradins University
• Manal H. Hamdan, Marquette UniversityFollow
• Nicola Alberto Valente, University of Cagliari
• Satoshi Yamaguchi, Osaka University
• Fahad Umer, The Aga Khan University
• Antonin Tichy, LMU Klinikum
• Ruben Pauwels, Aarhus University
• Falk Schwendicke, LMU Klinikum

Document Type

Article

Publication Date

9-2025

Publisher

Elsevier

Source Publication

Journal of Dentistry

Source ISSN

0300-5712

Original Item ID

DOI: 10.1016/j.jdent.2025.105867

Abstract

Objective

Artificial intelligence (AI) is increasingly used in dental research for diagnosis, treatment planning, and disease prediction. However, many dental AI studies lack methodological rigor, transparency, or reproducibility, and no dedicated peer-review guidance exists for this field.

Methods

Editors and reviewers from the ITU/WHO/WIPO AI for Health – Dentistry group participated in a structured survey and group discussions to identify key elements for reviewing AI dental research. A draft of the recommendations was circulated for feedback and consensus.

Results

The consensus from editors and reviewers identified four key indicators of high-quality AI dental research: (1) relevance to a real clinical or methodological problem, (2) robust and transparent methodology, (3) reproducibility through data/code availability or functional demos, and (4) adherence to ethical and responsible reporting practices. Common reasons for rejection included lack of novelty, poor methodology, limited external testing, and overstated claims. Four essential checks were proposed to support peer review: the study should address a meaningful clinical question, follow appropriate reporting guidelines (e.g., DENTAL-AI, STARD-AI), clearly describe reproducible methods, and use precise, justified, and clinically relevant wording.

Conclusion

Editors and reviewers play a critical role in improving the quality of AI research in dentistry. This guidance aims to support more robust peer review and contribute to the development of reliable, clinically relevant, and ethically sound AI applications in dentistry.

Comments

Journal of Dentistry, Vol. 160 (September 2025): 105867. DOI.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Recommended Citation

Uribe, Sergio E.; Hamdan, Manal H.; Valente, Nicola Alberto; Yamaguchi, Satoshi; Umer, Fahad; Tichy, Antonin; Pauwels, Ruben; and Schwendicke, Falk, "Evaluating Dental AI Research Papers: Key Considerations for Editors and Reviewers" (2025). School of Dentistry Faculty Research and Publications. 618.
https://epublications.marquette.edu/dentistry_fac/618