Artificial intelligence in salivary biomarker discovery and validation for oral diseases

• Published in: Oral diseases Vol. 30; no. 1; pp. 23 - 37
• Main Authors: Adeoye, John, Su, Yu‐Xiong
• Format: Journal Article
• Language: English
• Published: Denmark Wiley Subscription Services, Inc 01.01.2024
• Subjects: Artificial Intelligence; Biomarkers; Dental Caries; Humans; machine learning; Maxillofacial; maxillofacial conditions; Mouth Diseases - diagnosis; oral diseases; Periodontal diseases; Periodontal Diseases - diagnosis; salivary biomarkers; Salivary gland; maxillofacial conditions; oral diseases; machine learning; salivary biomarkers; artificial intelligence
• ISSN: 1354-523X; 1601-0825
• DOI: 10.1111/odi.14641

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.