MedTrace Logo

The Accuracy of Computer Aided Detection of Periapical Radiolucencies on Cone -Beam Computed Tomography Images Using Artificial Intelligence

NCT05538104 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 50

Last updated 2022-09-13

No results posted yet for this study

Summary

A diagnostic accuracy study to assess the accuracy of a newly developed deep learning model in the automatic detection of periapical radiolucent lesions of upper and lower jaws by comparing it with experienced radiologists' opinion, which represents the ground truth.

Hypothesis: The null hypothesis is that the results of the deep learning model are as accurate as the radiologists' opinion.

Conditions

  • Periapical Lesions

Sponsors & Collaborators

  • Cairo University

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-09-30
Primary Completion
2023-08-31
Completion
2023-12-31

More Related Trials

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 NCT05538104 on ClinicalTrials.gov