Raj Ruchika, Rajappa Ravikumar, Murthy Vijayalakshmi, Osanlouy Mahyar, Lawrence Daniel, Ganhewa Mahen, Cirillo Nicola
CoTreat, CoTreat Pty Ltd., Melbourne, VIC 3000, Australia.
Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, 720, Swanston Street, Carlton, VIC 3053, Australia.
Bioengineering (Basel). 2024 Dec 25;12(1):9. doi: 10.3390/bioengineering12010009.
Artificial intelligence (AI) has gained significant traction in medical image analysis, including dentistry, aiding clinicians in making timely and accurate diagnoses. Radiographs, such as orthopantomograms (OPGs) and intraoral radiographs, along with clinical photographs, are the primary imaging modalities employed for AI-powered analysis in the dental field. In this review, we discuss the most recent research and product developments concerning the clinical application of AI as a visual aid in dentistry and introduce the concept of Observational Diagnostics (ODs) as a structured method to standardise image analysis. ODs serve as foundational elements for AI-driven diagnostic aids and have the potential to improve the consistency and reliability of diagnostic data used in treatment planning. We provide illustrative examples to demonstrate how ODs not only represent a significant advancement towards more precise diagnostic aids but also provide the basis for the generation of evidence-based treatment recommendations. These OD-based algorithms have been integrated into chairside AI applications to streamline clinical workflows to improve consistency, accuracy, and efficiency.
人工智能（AI）在医学图像分析领域，包括牙科，已获得显著关注，有助于临床医生进行及时准确的诊断。口腔全景片（OPG）和口内X光片等X光片以及临床照片，是牙科领域用于人工智能驱动分析的主要成像方式。在本综述中，我们讨论了有关人工智能在牙科作为视觉辅助工具临床应用的最新研究和产品开发，并介绍了观察诊断法（ODs）这一标准化图像分析的结构化方法的概念。ODs作为人工智能驱动诊断辅助工具的基础要素，有可能提高治疗计划中使用的诊断数据的一致性和可靠性。我们提供了示例来说明ODs不仅代表了朝着更精确诊断辅助工具迈出的重大进步，还为基于证据的治疗建议的生成提供了基础。这些基于ODs的算法已集成到椅旁人工智能应用程序中，以简化临床工作流程，提高一致性、准确性和效率。
