Adeoye John, Su Yu-Xiong
Division of Oral and Maxillofacial Surgery, Faculty of Dentistry, University of Hong Kong, Hong Kong SAR, China.
Oral Dis. 2024 Jan;30(1):23-37. doi: 10.1111/odi.14641. Epub 2023 Jun 19.
Salivary biomarkers can improve the efficacy, efficiency, and timeliness of oral and maxillofacial disease diagnosis and monitoring. Oral and maxillofacial conditions in which salivary biomarkers have been utilized for disease-related outcomes include periodontal diseases, dental caries, oral cancer, temporomandibular joint dysfunction, and salivary gland diseases. However, given the equivocal accuracy of salivary biomarkers during validation, incorporating contemporary analytical techniques for biomarker selection and operationalization from the abundant multi-omics data available may help improve biomarker performance. Artificial intelligence represents one such advanced approach that may optimize the potential of salivary biomarkers to diagnose and manage oral and maxillofacial diseases. Therefore, this review summarized the role and current application of techniques based on artificial intelligence for salivary biomarker discovery and validation in oral and maxillofacial diseases.
唾液生物标志物可以提高口腔颌面部疾病诊断和监测的有效性、效率和及时性。已将唾液生物标志物用于疾病相关结果的口腔颌面部疾病包括牙周病、龋齿、口腔癌、颞下颌关节功能障碍和唾液腺疾病。然而，鉴于唾液生物标志物在验证过程中的准确性存在争议，利用现有的丰富多组学数据采用当代分析技术进行生物标志物的选择和操作，可能有助于提高生物标志物的性能。人工智能就是这样一种先进方法，它可以优化唾液生物标志物在诊断和管理口腔颌面部疾病方面的潜力。因此，本综述总结了基于人工智能的技术在口腔颌面部疾病唾液生物标志物发现和验证中的作用及当前应用。
