Szczegóły publikacji
Opis bibliograficzny
Evaluation of dental panoramic radiographs by artificial intelligence compared to human reference: a diagnostic accuracy study / Natalia Turosz, Kamila CHĘCIŃSKA, Maciej Chęciński, Marcin Sielski, Maciej Sikora // Journal of Clinical Medicine [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 2077-0383. — 2024 — vol. 13 iss. 22 art. no. 6859, s. 1–14. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 12–14, Abstr. — Publikacja dostępna online od: 2024-11-14. — K. Chęcińska - dod. afiliacje: WSB Academy, Dąbrowa Górnicza ; WSB Merito University in Poznan, Chorzów
Autorzy (5)
- Turosz Natalia
- AGHChęcińska Kamila
- Chęciński Maciej Adam
- Sielski Marcin
- Sikora Maciej
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 156741 |
|---|---|
| Data dodania do BaDAP | 2025-01-08 |
| Tekst źródłowy | URL |
| DOI | 10.3390/jcm13226859 |
| Rok publikacji | 2024 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Journal of Clinical Medicine |
Abstract
Background/Objectives: The role of artificial intelligence (AI) in dentistry is becoming increasingly significant, particularly in diagnosis and treatment planning. This study aimed to assess the sensitivity, specificity, accuracy, and precision of AI-driven software in analyzing dental panoramic radiographs (DPRs) in patients with permanent dentition. Methods: Out of 638 DPRs, 600 fulfilled the inclusion criteria. The radiographs were analyzed by AI software and two researchers. The following variables were assessed: (1) missing tooth, (2) root canal filling, (3) endodontic lesion, (4) implant, (5) abutment, (6) pontic, (7) crown, (8) and sound tooth. Results: The study revealed very high performance metrics for the AI algorithm in detecting missing teeth, root canal fillings, and implant abutment crowns, all greater than 90%. However, it demonstrated moderate sensitivity and precision in identifying endodontic lesions and the lowest precision (65.30%) in detecting crowns. Conclusions: AI software can be a valuable tool in clinical practice for diagnosis and treatment planning but may require additional verification by clinicians, especially for identifying endodontic lesions and crowns. Due to some limitations of the study, further research is recommended.
