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Article: Artificial intelligence in salivary biomarker discovery and validation for oral diseases

TitleArtificial intelligence in salivary biomarker discovery and validation for oral diseases
Authors
Adeoye, JohnSu, Yu‐Xiong
Keywordsartificial intelligence
machine learning
maxillofacial conditions
oral diseases
salivary biomarkers
Issue Date19-Jun-2023
PublisherWiley
Citation
Oral Diseases, 2023 How to Cite?
DOI: http://dx.doi.org/10.1111/odi.14641
Abstract

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.


Persistent Identifierhttp://hdl.handle.net/10722/331510
ISSN
1354-523X
2023 Impact Factor: 2.9
2023 SCImago Journal Rankings: 0.895
ISI Accession Number ID
WOS:001010331700001

 

DC FieldValueLanguage
dc.contributor.authorAdeoye, John-
dc.contributor.authorSu, Yu‐Xiong-
dc.date.accessioned2023-09-21T06:56:29Z-
dc.date.available2023-09-21T06:56:29Z-
dc.date.issued2023-06-19-
dc.identifier.citationOral Diseases, 2023-
dc.identifier.issn1354-523X-
dc.identifier.urihttp://hdl.handle.net/10722/331510-
dc.description.abstract<p>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.</p>-
dc.languageeng-
dc.publisherWiley-
dc.relation.ispartofOral Diseases-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectartificial intelligence-
dc.subjectmachine learning-
dc.subjectmaxillofacial conditions-
dc.subjectoral diseases-
dc.subjectsalivary biomarkers-
dc.titleArtificial intelligence in salivary biomarker discovery and validation for oral diseases-
dc.typeArticle-
dc.identifier.doi10.1111/odi.14641-
dc.identifier.scopuseid_2-s2.0-85162182683-
dc.identifier.eissn1601-0825-
dc.identifier.isiWOS:001010331700001-
dc.identifier.issnl1354-523X-

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