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    The Current State of Clinical Diagnostic Algorithms for Mucosal Oral Lesions: A Scoping Review

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    Oral Diseases - 2025 - Al‐Shehri - The Current State of Clinical Diagnostic Algorithms for Mucosal Oral Lesions A Scoping.pdf (722.2Kb)
    Date
    2025-06-02
    Author
    Al-Shehri, Mohammed
    Dillibabu, Theerthika
    Nicolau, Belinda
    Magalhaes, Marco
    Makhoul, Nicholas
    Tamimi, Faleh
    Chauvin, Peter
    Madathil, Sreenath
    ...show more authors ...show less authors
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    Abstract
    Background: Diagnosing oral lesions remains challenging for many dentists. Despite the availability of diagnostic algorithms, there is a dearth of comprehensive evidence synthesis and a discussion on their clinical and pedagogical applicability. Methods: A scoping review was conducted to identify: (1) algorithms or flow diagrams that help clinicians to diagnose oral lesions in a clinical setting without additional software; (2) publications in English; (3) all age groups; (4) algorithms for oral lesions of soft tissue only. We excluded those that are: (1) black-box; (2) required additional tests; (3) older versions; (4) for non-mucosal lesions, and (5) intended for self-screening. A keyword and MeSH term search was performed across three peer-reviewed publication databases and gray literature. Results: Seventeen algorithms from 15 peer-reviewed manuscripts and 1 online course were identified. Most studies did not mention how the algorithms were developed, and none had been validated in a clinical setting. The algorithms often focused on one or two types of lesions and were incomplete in differential diagnoses. Conclusion: Few clinical diagnostic algorithms for oral lesions are available in the literature. Notably, there are no validated and comprehensive clinical diagnostic algorithms for oral mucosal lesions.
    URI
    https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105007098734&origin=inward
    DOI/handle
    http://dx.doi.org/10.1111/odi.15388
    http://hdl.handle.net/10576/66662
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    • Dental Medicine Research [‎428‎ items ]

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