Endodontics is the dental specialty foremost concerned with diseases of the pulp and periradicular tissues. Clinicians often face patients with varying symptoms, must critically assess radiographic images in 2 and 3 dimensions, derive complex diagnoses and decision making, and deliver sophisticated treatment. Paired with low intra- and interobserver agreement for radiographic interpretation and variations in treatment outcome resulting from nonstandardized clinical techniques, there exists an unmet need for support in the form of artificial intelligence (AI), providing automated biomedical image analysis, decision support, and assistance during treatment. In the past decade, there has been a steady increase in AI studies in endodontics but limited clinical application. This review focuses on critically assessing the recent advancements in endodontic AI research for clinical applications, including the detection and diagnosis of endodontic pathologies such as periapical lesions, fractures and resorptions, as well as clinical treatment outcome predictions. It discusses the benefits of AI-assisted diagnosis, treatment planning and execution, and future directions including augmented reality and robotics. It critically reviews the limitations and challenges imposed by the nature of endodontic data sets, AI transparency and generalization, and potential ethical dilemmas. In the near future, AI will significantly affect the everyday endodontic workflow, education, and continuous learning.

中文翻译：

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人工智能在牙髓病学中的应用


牙髓病学是主要关注牙髓和神经根周围组织疾病的牙科专业。临床医生经常面对具有不同症状的患者，必须严格评估 2 维和 3 维影像学图像，得出复杂的诊断和决策，并提供复杂的治疗。再加上影像学解释的观察者内部和观察者间一致性低，以及非标准化临床技术导致的治疗结果变化，存在对人工智能 （AI） 形式的支持需求未得到满足，在治疗期间提供自动生物医学图像分析、决策支持和帮助。在过去十年中，牙髓学领域的人工智能研究稳步增加，但临床应用有限。本综述侧重于批判性评估牙髓 AI 研究在临床应用中的最新进展，包括根尖周病变、骨折和吸收等牙髓病变的检测和诊断，以及临床治疗结果预测。它讨论了 AI 辅助诊断、治疗计划和执行的好处，以及包括增强现实和机器人技术在内的未来方向。它批判性地回顾了牙髓数据集的性质、AI 透明度和泛化以及潜在的道德困境所带来的限制和挑战。在不久的将来，人工智能将对日常牙髓病工作流程、教育和持续学习产生重大影响。