Evaluating dental AI research papers: Key considerations for editors and reviewers
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.
Authors
- Antonín Tichý (ORCID: https://orcid.org/0000-0002-6260-9992)
- Fahad Umer (ORCID: https://orcid.org/0000-0003-3817-5941)
- Satoshi Yamaguchi (ORCID: https://orcid.org/0009-0004-8668-7364)
- Falk Schwendicke (ORCID: https://orcid.org/0000-0003-1223-1669)
- Nicola Alberto Valente (ORCID: https://orcid.org/0000-0003-1403-5274)
- Ruben Pauwels (ORCID: https://orcid.org/0000-0002-9462-7546)
- Sergio Uribe (ORCID: https://orcid.org/0000-0003-0684-2025)
- Manal Hamdan (ORCID: https://orcid.org/0000-0003-4081-7675)
Institutions
- Marquette University (US)
- University of Baghdad (IQ)
- Riga Technical University (LV)
- Aarhus University (DK)
- Charles University (CZ)
- Aga Khan University Hospital (PK)
- LMU Klinikum (DE)
- Riga Stradiņš University (LV)
- Ludwig-Maximilians-Universität München (DE)
- Osaka Dental University (JP)
Publication Details
- Journal
- Journal of Dentistry
- Published
- 2025-05-30
- DOI
- https://doi.org/10.1016/j.jdent.2025.105867
- Citations
- 9
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 5.89
Funders
- Deutsche Forschungsgemeinschaft
- Latvijas Zinātnes Padome
- Horizon 2020 Framework Programme
- HORIZON EUROPE Framework Programme