Skip to main navigation menu Skip to main content Skip to site footer

A NOVEL MODEL FOR EARLY DIAGNOSIS OF DENTAL DISEASES BASED ON ARTIFICIAL INTELLIGENCE AND SALIVARY BIOMARKERS

Abstract

Early diagnosis of dental diseases is crucial for preventing irreversible tissue damage and improving patient outcomes. Recent advancements in artificial intelligence (AI) combined with salivary biomarker analysis offer a promising approach for non-invasive, rapid, and accurate detection of oral pathologies. Salivary biomarkers, including proteins, enzymes, metabolites, and nucleic acids, reflect both local and systemic disease states. Integration of AI algorithms allows automated pattern recognition, predictive modeling, and individualized risk assessment based on complex biomarker profiles. This novel model enhances early detection of dental caries, periodontal diseases, and oral cancers, enabling personalized treatment strategies and improved preventive care [1, 2, 3].

Keywords

artificial intelligence, salivary biomarkers, early diagnosis, dental diseases, predictive modeling [4, 5]

PDF

References

  1. Zhang, A., Sun, H., Wang, P., Han, Y., & Wang, X. (2016). Saliva metabolomics opens door to biomarker discovery, disease diagnosis, and treatment. Analytical Chemistry, 88(21), 10632–10641.
  2. Kaufman, E., & Lamster, I. B. (2002). Analysis of saliva for periodontal diagnosis—A review. Journal of Clinical Periodontology, 29(7), 487–496.
  3. Li, Y., St John, M. A., Zhou, X., Kim, Y., Sinha, U., Jordan, R. C., ... & Wong, D. T. (2004). Salivary transcriptome diagnostics for oral cancer detection. Clinical Cancer Research, 10(24), 8442–8450.
  4. Wong, D. T. (2006). Salivary diagnostics powered by nanotechnologies, proteomics, and genomics. Journal of the American Dental Association, 137(3), 313–321.
  5. Schwendicke, F., Samek, W., & Krois, J. (2020). Artificial intelligence in dentistry: chances and challenges. Journal of Dental Research, 99(7), 769–774.
  6. de Lima, L. A., & Bittencourt, B. A. (2021). Machine learning approaches for salivary biomarker-based diagnosis of oral diseases. Oral Diseases, 27(3), 548–556.
  7. Gursoy, U. K., & Könönen, E. (2012). Salivary biomarkers: non-invasive indicators for monitoring oral health and systemic diseases. Journal of Clinical Periodontology, 39(7), 636–645.
  8. Lee, Y. H., & Wong, D. T. (2009). Saliva: an emerging biofluid for early detection of diseases. American Journal of Dentistry, 22(4), 241–248.
  9. Taba, M., Kinney, J., Kim, A., & Giannobile, W. V. (2005). Diagnostic biomarkers for oral and periodontal diseases. Dental Clinics of North America, 49(3), 551–571.
  10. Krois, J., Ekert, T., Meinhold, L., & Schwendicke, F. (2019). Deep learning for the radiographic detection of periodontal bone loss. Journal of Clinical Periodontology, 46(1), 43–52.

Downloads

Download data is not yet available.