Health Technology/clinical-trials

Deep Learning Framework for Keratinized Gingiva Assessment: Can AI Standardise Periodontal Measurement in Clinical Practice?

247 Health News Editorial

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26 July 2026

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4 min read

·clinical-trials

A 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. 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. 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
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  4. 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. 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. 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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