No Code Artificial Intelligence to Detect Radiographic Features Associated With Unsatisfactory Endodontic Treatment

NANot yet recruitingINTERVENTIONAL
Enrollment

80

Participants

Timeline

Start Date

July 30, 2024

Primary Completion Date

November 13, 2024

Study Completion Date

December 13, 2024

Conditions
Endodontically Treated TeethEndodontic UnderfillEndodontic OverfillApical Periodontitis
Interventions
DEVICE

AI guidance for finding radiographic features

A secured website was made for the trial in which each student could log in using the assigned number. All the image datasets were uploaded to this website. The students will be randomly assigned to the experiment and control group. Both students were asked to segment the features associated with the quality of root canal treatment and predict the prognosis of treatment while the experiment group had access to AI guidance and the control group didn't.

All Listed Sponsors
collaborator

Queen Mary University of London

OTHER

lead

University of Copenhagen

OTHER

NCT06450938 - No Code Artificial Intelligence to Detect Radiographic Features Associated With Unsatisfactory Endodontic Treatment | Biotech Hunter | Biotech Hunter