Status:
UNKNOWN
Accuracy of Artificial Intelligence in Evaluation of the Relationship Between Mandibular Third Molar and Mandibular Canal on CBCT
Lead Sponsor:
Cairo University
Conditions:
Artificial Intelligence
Eligibility:
All Genders
25-65 years
Brief 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 i...
Detailed Description
The mandibular third molar extraction, considered one of the most common surgeries in oral and maxillofacial field, it can be associated with several postoperative complications, like pain, bleeding, ...
Eligibility Criteria
Inclusion
- • CBCT Scans showing Mandibular third molar of patients aging from 25 to 65 years old
- The FOV should clearly show the third molar completely with its roots and the IAN.
- Voxel size of 0.2mm.
- Mandibular third molars. Absence of artifacts, dental implants in the adjacent teeth.
Exclusion
- • CBCT images of sub-optimal quality or artifacts/high scatter interfering with proper assessment.
Key Trial Info
Start Date :
May 1 2022
Trial Type :
OBSERVATIONAL
Allocation :
ESTIMATED
End Date :
December 1 2023
Estimated Enrollment :
50 Patients enrolled
Trial Details
Trial ID
NCT05350228
Start Date
May 1 2022
End Date
December 1 2023
Last Update
April 28 2022
Active Locations (1)
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1
Faculty of dentistry cairo university
Cairo, Egypt, 12611