Skip to main content
Clinical Trials/NCT05912361
NCT05912361CompletedNot Applicable

The Impact of Training Dental Students for Using a Novel Artificial Intelligence-based Platform for Pulp Exposure Prediction Before Deep Caries Excavation: A Randomized Controlled Trial

University of Copenhagen2 sites in 1 country20 target enrollmentStarted: August 20, 2023Last updated:
Conditions

Trial Snapshot

Phase
Not Applicable
Status
Completed
Enrollment
20
Locations
2
Primary Endpoint
Performance of students at pulp exposure prediction in the AI-based platform with and without training session based on their sensitivity

Study Overview

Brief Summary

The emergence of artificial intelligence (AI) and specifically deep learning (DL) have shown great potentials in finding radiographic features and treatment planning in the field of cariology and endodontics . A growing body of literature suggests that DL models might assist dental practitioners in detecting radiographical features such as carious lesions, periapical lesions, as well as predicting the risk of pulp exposure when doing caries excavation therapy. Although, current literature lacks sufficient research on the effect of sufficient training of dental practitioners for using AI-based platforms. This prospective randomized controlled trial aims to assess the performance of students when using an AI-based platform for pulp exposure prediction with and without sufficient preprocedural training. The hypothesis is that participants performance at group with sufficient training is similar to the group without sufficient training.

Study Design

Study Type
Interventional
Allocation
Randomized
Intervention Model
Parallel
Primary Purpose
Other
Masking
Double (Participant, Outcomes Assessor)

Eligibility Criteria

Ages
20 Years to — (Adult, Older Adult)
Sex
All
Accepts Healthy Volunteers
Yes

Inclusion Criteria

  • perhaps 4th year and 5th year dental students at the university of Copenhagen who are willing to participate voluntarily and have signed the consent letter.
  • Limited or no previous knowledge and experience about AI

Exclusion Criteria

  • Not provided

Outcomes

Primary Outcomes

Performance of students at pulp exposure prediction in the AI-based platform with and without training session based on their sensitivity

Time Frame: 30 days

The sensitivity of students at both group (with and without training session) will be measured and compared together. It will be based on the proportion of actual pulp exposure cases that got predicted as pulp exposure (true positive).

Performance of students at pulp exposure prediction in the AI-based platform with and without training session based on their accuracy

Time Frame: 30 days

The accuracy of students at both group (with and without training session) will be measured and compared together. The accuracy measurement for each student will be calculated by the number of correct predictions of pulp exposure occurrence divided by the total predictions.

Performance of students at pulp exposure prediction in the AI-based platform with and without training session based on their specificity

Time Frame: 30 days

The specificity of students at both group (with and without training session) will be measured and compared together. It will be based on the proportion of actual 'no pulp exposure' cases correctly predicted as cases without pulp exposure (true negative).

Secondary Outcomes

No secondary outcomes reported

Investigators

Sponsor Class
Other
Responsible Party
Sponsor

Study Sites (2)

Loading locations...

Similar Trials