Imaging Science in Dentistry

  • 제54권4호
  • /
  • Pages.305-312
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  • 2024
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  • 2233-7822(pISSN)
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  • 2233-7830(eISSN)
대한영상치의학회 (Korean Academy of Oral and Maxillofacial Radiology)
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Artificial intelligence application in endodontics: A narrative review

  • Dennis Dennis (Department of Conservative Dentistry, Faculty of Dentistry, Universitas Sumatera Utara) ;
  • Siriwan Suebnukarn (Faculty of Dentistry, Thammasat University) ;
  • Min-Suk Heo (Department of Oral and Maxillofacial Radiology School of Dentistry, Seoul National University) ;
  • Trimurni Abidin (Department of Conservative Dentistry, Faculty of Dentistry, Universitas Sumatera Utara) ;
  • Cut Nurliza (Department of Conservative Dentistry, Faculty of Dentistry, Universitas Sumatera Utara) ;
  • Nevi Yanti (Department of Conservative Dentistry, Faculty of Dentistry, Universitas Sumatera Utara) ;
  • Wandania Farahanny (Department of Conservative Dentistry, Faculty of Dentistry, Universitas Sumatera Utara) ;
  • Widi Prasetia (Department of Conservative Dentistry, Faculty of Dentistry, Universitas Sumatera Utara) ;
  • Fitri Yunita Batubara (Department of Conservative Dentistry, Faculty of Dentistry, Universitas Sumatera Utara)
  • 투고 : 2024.03.21
  • 심사 : 2024.07.01
  • 발행 : 2024.12.31
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초록

Purpose: This review aimed to explore the scientific literature concerning the methodologies and applications of artificial intelligence (AI) in the field of endodontics. The findings may equip dentists with the necessary technical knowledge to understand the opportunities presented by AI. Materials and Methods: Articles published between 1992 and 2023 were retrieved through an electronic search of Medline via the PubMed, Scopus, and Google Scholar databases. The search, which was limited to articles published in English, aimed to identify relevant studies by employing the following keywords: "artificial intelligence," "machine learning," "deep learning," "endodontic," "root canal treatment," and "radiography." Ultimately, 71 studies that addressed the application of AI in endodontics were selected. Results: Numerous studies have demonstrated the effectiveness of AI applications in endodontics. These uses encompass the identification of root fractures and periapical lesions, assessment of working length, investigation of root canal system anatomy, prediction of retreatment success, and evaluation of dental pulp stem cell viability. Conclusion: AI technology is poised to advance aspects of endodontics including scheduling, patient care, management of drug-drug interactions, prognostic diagnosis, and the emerging area of robotic endodontic surgery. AI methods have demonstrated accuracy and precision in the identification, assessment, and prediction of diseases. Thus, AI can significantly improve endodontic diagnosis and treatment, increasing the overall efficacy of endodontic therapy.

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참고문헌

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