Szczegóły publikacji

Opis bibliograficzny

Oral health status and treatment needs based on artificial intelligence (AI) dental panoramic radiograph (DPR) analysis: a cross-sectional study / Natalia Turosz, Kamila CHĘCIŃSKA, Maciej Chęciński, Iwo Rutański, Marcin Sielski, Maciej Sikora // Journal of Clinical Medicine [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 2077-0383. — 2024 — vol. 13 iss. 13 art. no. 3686, s. 1–18. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 16–18, Abstr. — Publikacja dostępna online od: 2024-06-25

Autorzy (6)

Słowa kluczowe

public health dentistryartificial intelligenceDMF Indexdental radiographypanoramic radiography

Dane bibliometryczne

ID BaDAP154491
Data dodania do BaDAP2024-07-16
Tekst źródłowyURL
DOI10.3390/jcm13133686
Rok publikacji2024
Typ publikacjiartykuł w czasopiśmie
Otwarty dostęptak
Creative Commons
Czasopismo/seriaJournal of Clinical Medicine

Abstract

Background: The application of artificial intelligence (AI) is gaining popularity in modern dentistry. AI has been successfully used to interpret dental panoramic radiographs (DPRs) and quickly screen large groups of patients. This cross-sectional study aimed to perform a population-based assessment of the oral health status and treatment needs of the residents of Kielce, Poland, and the surrounding area based on DPR analysis performed by a high-accuracy AI algorithm trained with over 250,000 radiographs. Methods: This study included adults who had a panoramic radiograph performed, regardless of indications. The following diagnoses were used for analysis: (1) dental caries, (2) missing tooth, (3) dental filling, (4) root canal filling, (5) endodontic lesion, (6) implant, (7) implant abutment crown, (8) pontic crown, (9) dental abutment crown, and (10) sound tooth. The study sample included 980 subjects. Results: The patients had an average of 15 sound teeth, with the domination of the lower dental arch over the upper one. The most commonly identified pathology was dental caries, which affected 99% of participants. A total of 67% of patients underwent root canal treatment. Every fifth endodontically treated tooth presented a periapical lesion. Of study group members, 82% lost at least one tooth. Pontics were identified more often (9%) than implants (2%) in replacing missing teeth. Conclusions: DPR assessment by AI has proven to be an efficient method for population analysis. Despite recent improvements in the oral health status of Polish residents, its level is still unsatisfactory and suggests the need to improve oral health. However, due to some limitations of this study, the results should be interpreted with caution.

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