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Traditional diagnostic techniques tend to be long and dependent upon the availability of healthcare professionals and hence promote development of alternatives involving artificial intelligence (AI). This work aimed to evaluate the effectiveness of the application titled HI Bogi that embeds the model known as YOLOv8 in distinguishing dental caries among primary school pupils in Cimahi, Indonesia.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>A cross-sectional analytic model with prospectively collected data was adopted. A dataset consisting of 3,221 JPG photographs was created and labeled based on the International Caries Detection and Assessment System (ICDAS, D0 - D6) using Roboflow software. The photographs were resized to a size of 640\u2009\u00d7\u2009640 pixels and distributed into training (2,266 photographs), validation (635 photographs), and testing (320 photographs) sets. A YOLOv8x algorithm was used for application in deep learning tasks, and its performance was determined through mean Average Precision (mAP), Intersection over Union (IoU) measurements, and precision and recall metrics. Additionally, a Mann Whitney statistical test was carried out to contrast classification efficiency between the AI system and dental practitioners\u2019 classification efficacy, while both methods\u2019 diagnostic speed was tested.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      mAP was 45.8%, and precision was 72.6%, and recall was 41.1% for YOLOv8x model. Comparative testing across ICDAS categories did not vary significantly between dentists and AI (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&gt;\u20090.05). Detection of caries (D1\u2013D6) was observed to have a sensitivity ranged from 82.31% to 96.45% and specificity ranged from 77.10% to 99.33% on new data. Additionally, testing was completed approximately four times faster with AI compared to manual testing (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.000).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The YOLOv8x model in the HI Bogi app demonstrated diagnostic performance equal to dentists and a drastically shortened examination time, validating its use in school-based dental health programs. But class-specific precision variation suggests further refinement is needed. Further studies ought to increase datasets and characterize advanced architecture, such as transformer-based architecture, to achieve higher specificity and detection rates in rare lesion categories.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12903-025-07486-x","type":"journal-article","created":{"date-parts":[[2025,12,20]],"date-time":"2025-12-20T10:14:24Z","timestamp":1766225664000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Examination of new clinical dental caries in school children using real intra oral photos with artificial intelligence model YOLO-V8x"],"prefix":"10.1186","volume":"26","author":[{"given":"Rina Putri Noer","family":"Fadilah","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rasmi","family":"Rikmasari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saiful","family":"Akbar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arlette Suzy","family":"Setiawan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,12,20]]},"reference":[{"key":"7486_CR1","unstructured":"Kementerian Kesehatan. 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BMC Oral Health. 2023. https:\/\/doi.org\/10.1186\/s12903-023-03027-6.","journal-title":"BMC Oral Health"}],"container-title":["BMC Oral Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12903-025-07486-x","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12903-025-07486-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12903-025-07486-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T14:25:21Z","timestamp":1769437521000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s12903-025-07486-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,20]]},"references-count":55,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["7486"],"URL":"https:\/\/doi.org\/10.1186\/s12903-025-07486-x","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-5657504\/v1","asserted-by":"object"}]},"ISSN":["1472-6831"],"issn-type":[{"value":"1472-6831","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,20]]},"assertion":[{"value":"17 December 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 December 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This study was conducted in accordance with the ethical standards of the Declaration of Helsinki (1964, and its later amendments) and received ethical approval from the Research Ethics Committee of the Faculty of Dentistry, Padjadjaran University (approval number: 1291\/UN6.KEP\/EC\/2023; registration number: 2309051343; Clinical trial number: not applicable). Written informed consent to participate was obtained from the parents or legal guardians of all participating children under the age of 16 prior to data collection.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Written informed consent for publication of clinical details and\/or clinical images was obtained from the parents or legal guardians of all participating children under the age of 16.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"164"}}