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NCT06760104

Comparative Accuracy of AI Models and Clinical Assessment for Dental Plaque Detection in Children

Not yet recruiting Last updated 6 January 2025
What this trial tests

trial testing Dental Plaque Detection Using AI Models in Dental Plaque in 323 participants. Not yet recruiting.

Timeline
1 January 2025
Primary endpoint
30 December 2025
30 December 2025

Quick facts

Lead sponsorNaema Ahmed
StatusNot yet recruiting
Study typeOBSERVATIONAL
Enrollment323
Start date1 January 2025
Primary completion30 December 2025
Estimated completion30 December 2025
Sites1 location across Egypt

Drugs / interventions tested

Conditions studied

Sponsor

Naema Ahmed

Who can join

Adults 7 to 12, any sex, with Dental Plaque. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

This diagnostic accuracy study aims to evaluate the effectiveness of various artificial intelligence models in detecting dental plaque from intraoral images compared to clinical assessments performed by dentists among children. The study seeks to determine the accuracy, sensitivity, specificity, and overall performance of AI technologies in identifying dental plaque. study study Design: Observational study

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other recruiting trials for Dental Plaque

Currently open trials in the same condition.

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Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06760104.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing