{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T18:55:38Z","timestamp":1791658538174,"version":"4.3.4"},"update-to":[{"DOI":"10.12688\/f1000research.172671.1","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T00:00:00Z","timestamp":1772668800000}}],"reference-count":55,"publisher":"F1000 Research Ltd","license":[{"start":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T00:00:00Z","timestamp":1772668800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["f1000research.com"],"crossmark-restriction":false},"short-container-title":["F1000Res"],"abstract":"<ns4:p>Background The emergence of AI technologies has revolutionised dentistry, with intraoral imaging being a key area for innovation. Despite advances and growing interest in applying AI algorithms to intraoral x-rays, the methodological quality, diagnostic validity, and clinical applicability of existing studies remain unclear. Aim To synthesise and critically appraise the current evidence on AI integrated with intraoral digital radiographic imaging for detecting dental caries in adults, focusing on diagnostic accuracy compared with gold-standard methods and examining methodological quality, clinical applicability, and implementation challenges. Methods Following the JBI scoping review framework and PRISMA-ScR reporting guidelines, a comprehensive literature search was conducted across the PubMed, Scopus, and IEEE Xplore databases from January 2015 to May 2025. Studies that met the predefined eligibility criteria were included. Thematic analysis, combining inductive and deductive approaches following Braun and Clarke\u2019s framework, identified five themes. The CASP quality appraisal was performed to ensure methodological rigour. Results Ten peer-reviewed studies were included in the final data analysis. AI systems detected a greater number of carious lesions than human clinicians, particularly in early-stage caries, with representative metrics including 88% sensitivity, 91% specificity, and 89% accuracy. Other models reported F1-scores up to 89% and AUC \u224895%. Methodological diversity was notable, with histology-validated designs providing the strongest evidence. Implementation challenges included limited external and real-world validation, clinician oversight, ethical\/regulatory considerations, and inadequate model interpretability. Conclusion AI exhibits strong potential to enhance early caries detection on intraoral radiographs and support clinical decision-making in adults. Fully realising AI\u2019s clinical potential requires overcoming implementation and methodological challenges. Standardised validation methods across diverse populations and settings are crucial to ensure AI diagnostic reliability and generalisability. Current AI applications in dentistry are primarily designed to assist clinicians in detecting caries; however, their greatest potential lies in a future where they can independently guide treatment planning decisions.<\/ns4:p>","DOI":"10.12688\/f1000research.172671.2","type":"journal-article","created":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T11:59:07Z","timestamp":1772711947000},"page":"1328","update-policy":"https:\/\/doi.org\/10.12688\/f1000research.crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Artificial Intelligence Integrated with Intraoral Digital Imaging in Dental Caries Detection, Treatment Planning, and Clinical Decision-Making: A Scoping Review"],"prefix":"10.12688","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-7601-1325","authenticated-orcid":false,"given":"Sarah","family":"Kayali","sequence":"first","affiliation":[{"name":"Institute of Dentistry London England E1 2AH Queen Mary University of London"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6779-7902","authenticated-orcid":false,"given":"Ali","family":"Golkari","sequence":"additional","affiliation":[{"name":"Institute of Dentistry London England E1 2AH Queen Mary University of London"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manu","family":"Mathur","sequence":"additional","affiliation":[{"name":"Institute of Dentistry London England E1 2AH Queen Mary University of London"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2560","published-online":{"date-parts":[[2026,3,5]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"3649","DOI":"10.3390\/diagnostics13243649","article-title":"Detection, diagnosis, and monitoring of early caries: the future of individualised dental care.","volume":"13","author":"M Abdelaziz","year":"2023 Dec 12","journal-title":"Diagnostics."},{"key":"ref2","doi-asserted-by":"publisher","first-page":"247-259","DOI":"10.1159\/000516084","article-title":"Detection methods for early caries diagnosis: a systematic review and meta-analysis.","volume":"55","author":"P Foros","year":"2021 Aug 3","journal-title":"Caries Res."},{"key":"ref3","doi-asserted-by":"publisher","first-page":"1-15","DOI":"10.1155\/2023\/9365845","article-title":"Dental caries and its management.","volume":"2023","author":"A Warreth","year":"2023 Jan 3","journal-title":"Int. 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Please see below a point by point response to the comments.  \n<b>1. Definition of diagnostic metrics:<\/b> In response to this suggestion, we have now explicitly defined all diagnostic performance metrics (sensitivity, specificity, accuracy, precision, positive predictive value [PPV], negative predictive value [NPV], F1-score, and area under the curve [AUC]) at their first occurrence in the Methods section. Subsequent references to these metrics in the Results section now refer back to these definitions to enhance clarity and accessibility for general dental practitioners and non-technical readers.  \n<b>2. Clarification of anatomical scope (proximal vs. buccal\/occlusal caries)<\/b> We appreciate this important observation. Although the inclusion criteria did not restrict caries detection to a specific anatomical surface, the primary studies meeting eligibility criteria predominantly evaluated proximal caries using bitewing radiographs. Buccal and occlusal lesions were not adequately represented in the included evidence base.  \n<b>To address this, we have:<\/b> 1. Clarified in the Discussion that the reported AI performance metrics relate primarily to proximal caries detection. 2. Added a statement to the Limitations section acknowledging that buccal and occlusal caries\u2014particularly buccal lesions, which may be underdiagnosed radiographically due to anatomical overlap\u2014were underrepresented. 3. Revised the Conclusion to specify that the supporting diagnostic performance data relate to proximal caries rather than dental caries in general. We believe these revisions improve the precision, transparency, and clinical interpretation of the findings. However, we greatly appreciate any further comment that can help improve the quality of this manuscript.","URL":"https:\/\/f1000research.com\/articles\/14-1328\/v2#referee-comment-15552","order":1,"name":"referee-comment-15552","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.5256\/f1000research.190413.r449986, Patricio Melendez Rojas, Universidad de Valpara\u00edso, Valpara\u00edso, 03 Feb 2026, version 1, 1 approved, 1 approved with reservations","URL":"https:\/\/f1000research.com\/articles\/14-1328\/v1#referee-response-449986","order":2,"name":"referee-response-449986","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>Ali Golkari<\/b>; \n<i>Posted: 26 Feb 2026<\/i>; The authors sincerely thank the respected reviewer for accepting the peer-review and for the time they have spent to go through the manuscript in detail and provide us with such a valuable and constructive comment. The authors have done their best to amend the manuscript based on the reviewer\u2019s comments and hope the changes are acceptable. However, any further comment or feedback is welcome. Please see below a point by point response:  \n<b>Comment 1: Enhance Technical Accessibility<\/b> Thank you for this valuable suggestion. We have now explicitly defined all diagnostic performance metrics at their first occurrence in the manuscript's methods section to enhance accessibility for general dental practitioners and non-technical readers.  \n<b>Comment 2: Clarify Anatomical Scope<\/b> We thank the reviewer for highlighting this important limitation. We have revised the Discussion, Limitations and Conclusions sections to explicitly state that the reported diagnostic performance metrics primarily relate to proximal caries detection and that buccal and occlusal lesions were inadequately represented in the included studies.  \n<b>Comment 3: Standardize Reporting of Reference Methods<\/b> We thank the reviewer for this helpful suggestion. We would like to clarify that Table 3 already includes a dedicated column specifying the reference standard (gold standard) used in each study, such as histological validation or expert consensus.  \n<b>Comment 4: Expand Discussion on Implementation Barriers<\/b> Thank you for this important observation. We have expanded the Discussion section to provide a more detailed analysis of reliance on single-centre datasets, the lack of external and multicentre validation in dental AI research, and their implications for clinical generalisability and regulatory approval.  \n<b>Comment 5: Streamline and Decompartmentalize Table 3<\/b> We thank the reviewer for this thoughtful suggestion and appreciate the concern regarding the density of this table. While we carefully considered reorganising the table into separate thematic sub-tables, we found that study characteristics, reference standards, and diagnostic performance outcomes are closely interrelated and are most meaningfully interpreted together. Separating these elements would risk fragmenting the key contextual information required to interpret reported accuracy measures appropriately within each study\u2019s methodological framework.  \n<b>Comment 6: Full Transparency of Search Strings<\/b> We thank the reviewer for this recommendation. In accordance with PRISMA-ScR best practices, we have now included the complete, verbatim PubMed search strategy in the Methods to ensure full transparency and reproducibility.  \n<b>Comment 7: Consolidate Quality Appraisal Tables<\/b> We agree with this suggestion. More details as a concise narrative summary of the overall quality appraisal in now included in the result section. The CASP appraisal tables have originally uploaded as appendices when submitting the paper. The journal brought them into the main text. We will ask the production team to see if they can move them to appendices.","URL":"https:\/\/f1000research.com\/articles\/14-1328\/v2#referee-comment-15553","order":3,"name":"referee-comment-15553","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.5256\/f1000research.197199.r485638, Pankaj Kukreja, Al Baha University, Al Bahah, Al Bahah Province, 18 Jun 2026, version 2, indexed","URL":"https:\/\/f1000research.com\/articles\/14-1328\/v2#referee-response-485638","order":4,"name":"referee-response-485638","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"The author(s) declared that no grants were involved in supporting this work","order":5,"name":"grant-information","label":"Grant Information"},{"value":"This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","order":0,"name":"copyright-info","label":"Copyright"}]}}