MedTrace Logo

Accuracy of Artificial Intelligence in Evaluation of the Relationship Between Mandibular Third Molar and Mandibular Canal on CBCT

NCT05350228 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 50

Last updated 2022-04-28

No results posted yet for this study

Summary

Convolutional neural network (CNN) are computer applications that assist in the detection and/or diagnosis of diseases by providing an unbiased "second opinion" to the image interpreter10, aiming at improving accuracy and reducing time for analysis. With the rapid growth of Deep Learning (DL) algorithms in image-based applications, CAD systems can now be trained by DL to provide more advanced capability (i.e., the capability of artificial intelligence \[AI\]) to best assist clinicians).

Conditions

  • Artificial Intelligence

Interventions

DIAGNOSTIC_TEST

CNN based model

It is an automatic detector model based on convolution neural network created by computer science expert

Sponsors & Collaborators

  • Cairo University

    lead OTHER

Principal Investigators

  • Enas Anter · Cairo University

Eligibility

Min Age
25 Years
Max Age
65 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-05-31
Primary Completion
2023-12-31
Completion
2023-12-31

Countries

  • Egypt

Study Locations

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 NCT05350228 on ClinicalTrials.gov