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Artificial Intelligence Versus Clinical Examination in White Spot Lesions Detection, Identification, And Scoring

NCT07639749 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 329

Last updated 2026-06-10

No results posted yet for this study

Summary

The goal of this observational study is to compare the diagnostic accuracy of Clinical examination as a standard for detection, identification and scoring of White Spot Lesions Versus Artificial intelligence analysis of intraoral photographs. The photographs are examined by experienced dental professionals to maintain diagnostic accuracy. Machine learning models YOLO and Mask-RCNN will analyze these images in three phases: pre-analytical, analytical and post-analytical. A dataset of 329 labelled photographs, annotated by experts, is used to train these models. Data augmentation methods enhance model performance, and accuracy is assessed against clinical examination results to confirm reliability.

The main question it aims to answer is:

\- Is artificial intelligence analysis of intraoral photographs as accurate as clinical assessment in the detection, identification, and scoring of white spot lesions among adult Egyptian patients attending Cairo University Dental Hospital?

Conditions

  • White Spot Lesion of Tooth

Interventions

OTHER

Artificial Intelligence models (YOLO and MASK-RCNN)

Machine learning model well be used for assessment of intraoral photographs for the detection, identification, and scoring of white spot lesions in teeth

Sponsors & Collaborators

  • Cairo University

    lead OTHER

Principal Investigators

  • Asmaa A. Mohamed Yassen · Professor of Conservative Dentistry Department, Faculty of Dentistry, Cairo University

  • Rawda Hesham Abdelaziz · Associate Professor of Conservative Dentistry Department, Faculty of Dentistry, Cairo University

  • Asmaa A. Elsayed Osman · Lecturer of Information Technology, Faculty of Computers and Artificial Intelligence, Cairo University

Eligibility

Min Age
20 Years
Max Age
60 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-07-01
Primary Completion
2027-07-01
Completion
2027-11-01

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07639749 on ClinicalTrials.gov