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Evaluating dental AI research papers: Key considerations for editors and reviewers

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11110%2F25%3A10499976" target="_blank" >RIV/00216208:11110/25:10499976 - isvavai.cz</a>

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=NlAEgan-h8" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=NlAEgan-h8</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.jdent.2025.105867" target="_blank" >10.1016/j.jdent.2025.105867</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Evaluating dental AI research papers: Key considerations for editors and reviewers

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    30208 - Dentistry, oral surgery and medicine

Result continuities

  • Project

  • Continuities

    V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Journal of Dentistry

  • ISSN

    0300-5712

  • e-ISSN

    1879-176X

  • Volume of the periodical

    160

  • Issue of the periodical within the volume

    September

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    6

  • Pages from-to

    105867

  • UT code for WoS article

    001513409700008

  • EID of the result in the Scopus database

    2-s2.0-105008120382