Deep Learning Framework for Keratinized Gingiva Assessment: Can AI Standardise Periodontal Measurement in Clinical Practice?
247 Health News Editorial
·26 July 2026
·4 min read
·clinical-trialsA completed diagnostic validation study from Al-Azhar University has evaluated a deep learning framework capable of automatically measuring keratinized gingiva width from smartphone-acquired intraoral photographs. The research addresses longstanding inter-examiner variability in periodontal tissue assessment and could inform future integration of AI-based tools into routine dental clinical workflows.
Originally reported by ClinicalTrials.gov
References
- 1.Al-Azhar University. (2024). A deep learning-based analytical framework for detection, quantification, and quality assessment of keratinized gingival tissues in clinical examination images. ClinicalTrials.gov. https://clinicaltrials.gov/study/NCT07689552
- 2.Scheyer, E. T., Sanz, M., Dibart, S., Greenwell, H., John, V., Kim, D. M., Langer, L., Rasperini, G., & Sharaf, M. (2015). Periodontal soft tissue non-root coverage procedures: A consensus report from the AAP Regeneration Workshop. Journal of Periodontology, 86(2 Suppl), S73–S76. https://doi.org/10.1902/jop.2015.140376
- 3.Ronneberger, O., Fischer, P., & Brox, T. (2015). U-Net: Convolutional networks for biomedical image segmentation. In N. Navab, J. Hornegger, W. Wells, & A. Frangi (Eds.), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015, Lecture Notes in Computer Science (Vol. 9351, pp. 234–241). Springer. https://doi.org/10.1007/978-3-319-24574-4_28
- 4.Lee, J. H., Kim, D. H., Jeong, S. N., & Choi, S. H. (2018). Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm. Journal of Dentistry, 77, 106–111. https://doi.org/10.1016/j.jdent.2018.07.015
- 5.GBD 2017 Oral Disorders Collaborators. (2020). Global, regional, and national levels and trends in burden of oral conditions from 1990 to 2017: A systematic analysis for the Global Burden of Disease 2017 study. Journal of Dental Research, 99(4), 362–373. https://doi.org/10.1177/0022034520908533
- 6.Zweers, J., Thomas, R. Z., Slot, D. E., Weisgold, A. S., & Van der Weijden, F. G. (2014). Characteristics of periodontal biotype, its dimensions, associations and prevalence: A systematic review. Journal of Clinical Periodontology, 41(10), 958–971. https://doi.org/10.1111/jcpe.12275
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247 Health News Editorial
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