Dennis Dennis, Suebnukarn Siriwan, Heo Min-Suk, Abidin Trimurni, Nurliza Cut, Yanti Nevi, Farahanny Wandania, Prasetia Widi, Batubara Fitri Yunita
Department of Conservative Dentistry, Faculty of Dentistry, Universitas Sumatera Utara, Medan, Indonesia.
Faculty of Dentistry, Thammasat University, Pathumthani 12121, Bangkok, Thailand.
Imaging Sci Dent. 2024 Dec;54(4):305-312. doi: 10.5624/isd.20240321. Epub 2024 Aug 25.
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.
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.
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.
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.
本综述旨在探索有关人工智能（AI）在牙髓病学领域的方法和应用的科学文献。这些研究结果可为牙医提供必要的技术知识，以了解人工智能带来的机遇。
通过PubMed、Scopus和谷歌学术数据库对Medline进行电子检索，获取1992年至2023年发表的文章。该检索仅限于英文发表的文章，旨在通过使用以下关键词识别相关研究：“人工智能”、“机器学习”、“深度学习”、“牙髓病学”、“根管治疗”和“放射摄影”。最终，筛选出71项涉及人工智能在牙髓病学中应用的研究。
大量研究证明了人工智能在牙髓病学应用中的有效性。这些应用包括根折和根尖周病变的识别、工作长度的评估、根管系统解剖结构的研究、再治疗成功率的预测以及牙髓干细胞活力的评估。
人工智能技术有望推动牙髓病学在包括日程安排、患者护理、药物相互作用管理、预后诊断以及新兴的机器人牙髓手术领域等方面的发展。人工智能方法在疾病的识别、评估和预测方面已证明具有准确性和精确性。因此，人工智能可显著改善牙髓病的诊断和治疗，提高牙髓治疗的整体疗效。
