Impact of Training Dental Students for an AI-Based Platform

January 5, 2024 updated by: University of Copenhagen

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

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 Overview

Study Type

Interventional

Enrollment (Actual)

20

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

      • Copenhagen, Denmark, 2200
        • University of Copenhagen Department of Odontology Cariology and Endodontics Section for Clinical Oral Microbiology

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

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:

  • None

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Other
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Double

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Students using AI-platform for assessing the risk of pulp exposure receiving a training session

Students will go through a one-hour hands-on training session before taking the test at the online platform. The session includes a theoretical session related to basic aspects of AI in radiology, CNN (Convolutional Neural Network) applications for cariology and endodontics, as well as basics of excavation therapy and pulp exposure. the theoretical part will be followed by a hands on session on which participants check 11 cases of teeth with deep caries and will find the closest line between caries and pulp.

Then, they will receive access to log in to the website on which pretreatment x-rays of cases undergoing caries excavation therapy is uploaded. The performance of students on will be assessed.

The students at the experimental group will receive a one-hour hands-on training session before logging in to the online platform. The session will be presented by a dentist with AI experience and this session will present basic aspects of AI in radiology, deep learning (DL) applications for cariology and endodontics, as well as basics of excavation therapy and pulp exposure. the theoretical part will be followed by a hands on session on which each participant will check 11 cases of teeth with deep caries and will find the closest line between caries and pulp. their performance will be supervised by the training session presenter and the correct line will be shown them in case of making wrong line.
No Intervention: Students using AI-platform for assessing the risk of pulp exposure without any training session
Students will not receive any training before starting the experiment. Only a 5-minute video will be played as the guide for answering the questions in the website. Then, they will receive access to log in to the website on which pretreatment x-rays of cases undergoing caries excavation therapy is uploaded. The performance of students on will be assessed.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
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.
30 days
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).
30 days
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).
30 days

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

August 20, 2023

Primary Completion (Actual)

December 20, 2023

Study Completion (Actual)

January 1, 2024

Study Registration Dates

First Submitted

May 24, 2023

First Submitted That Met QC Criteria

June 12, 2023

First Posted (Actual)

June 22, 2023

Study Record Updates

Last Update Posted (Estimated)

January 8, 2024

Last Update Submitted That Met QC Criteria

January 5, 2024

Last Verified

January 1, 2024

More Information

Terms related to this study

Other Study ID Numbers

  • 504-0342/22-5000

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on Artificial Intelligence

Subscribe