A Deep Learning-Based Analytical Framework for Detection, Quantification, and Quality Assessment of Keratinized Gingival Tissues in Clinical Examination Images
Sponsor study identifier
observational
50
1 country
1
Study Start
July 1, 2025
Actual (reported)Primary Completion
January 9, 2026
Actual (reported)Study Completion
March 15, 2026
Actual (reported)This study aims to develop and validate an artificial intelligence-based system for automated measurement of keratinized gingiva width using smartphone-acquired intraoral clinical photographs. Standardized intraoral images will be collected and analyzed using a deep learning model, and the results will be compared with clinical measurements performed by calibrated expert examiners, which serve as the reference standard. The performance of the proposed system will be evaluated using accuracy metrics including Dice coefficient, Intersection over Union (IoU), precision, recall, and F1-score. This study seeks to support the integration of AI tools into periodontal diagnosis and clinical decision-making to improve measurement consistency and reduce inter-examiner variability.
Registry-reported information. Elapsed time and enrollment totals alone do not measure study progress or recruitment pace.
March 15, 2026
Actual (reported)Click on a node to explore related trials.
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Dates and qualifiers reported by the registry. Estimated dates do not confirm that a milestone has occurred.
July 1, 2025
Actual (reported)January 9, 2026
Actual (reported)March 15, 2026
Actual (reported)June 30, 2026
Actual (reported)July 8, 2026
Actual (reported)Accuracy of Artificial Intelligence-Based Keratinized Gingiva Width Measurement
Evaluation of the agreement between keratinized gingiva width measurements generated by the artificial intelligence model and reference measurements obtained by calibrated examiners using smartphone-acquired intraoral clinical photographs at the baseline clinical visit.
Baseline (single study visit)
Participants whose smartphone-acquired intraoral clinical photographs were used for assessment of keratinized gingiva width. Clinical measurements performed by expert examiners served as the reference standard for validation of the artificial intelligence model.
Analysis of smartphone-acquired intraoral photographs using a deep learning model for automated measurement of keratinized gingiva width.
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Participants attending the clinic of the department of Periodontologly Faculty of Dental Medicine for girls Al-Azhar university who met the study eligibility criteria and provided smartphone-acquired intraoral clinical photographs for keratinized gingiva width assessment and artificial intelligence model validation.
Faculty of Dental Medicine for Girls, Al-Azhar University
Cairo, Cairo Governorate, 11754, Egypt
50 participants (actual enrollment reported by the registry).
First Submitted
June 30, 2026
First Posted
July 8, 2026
Study Start
July 1, 2025
Actual (reported)Locally Delivered Melatonin Gel in Management of Stage II Grade B Periodontitis
Contact the study team to confirm eligibility.
Primary Completion
January 9, 2026
Actual (reported)Study Completion
March 15, 2026
Actual (reported)Last Updated
July 8, 2026
Record last verified: 2026-07
IPD will not be shared to protect patient confidentiality and in compliance with institutional ethical guidelines. Data access is limited to the study investigators only.
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Source: ClinicalTrials.gov.
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