Impact of Training Dental Students for an AI-Based Platform

Artificial Intelligence Clinical Trial

Official title:

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

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT05912361
• Other study ID #: 504-0342/22-5000
• Status: Completed
• Phase: N/A
• Start date: August 20, 2023
• Est. completion date: January 1, 2024

Study information

• Verified date: January 2024
• Source: University of Copenhagen
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 20
• Est. completion date: January 1, 2024
• Est. primary completion date: December 20, 2023
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 20 Years and older

Eligibility

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

Related Conditions & MeSH terms

• Artificial Intelligence
• Education

Intervention

Behavioral:
• receiving a one hour theoretical and hands on training session before using an AI-based platform
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.

Locations

Country	Name	City	State
Denmark	University of Copenhagen Department of Odontology Cariology and Endodontics Section for Clinical Oral Microbiology	Copenhagen

Sponsors (1)

Lead Sponsor	Collaborator
University of Copenhagen

Country where clinical trial is conducted

Denmark, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Performance of students at pulp exposure prediction in the AI-based platform with and without training session based on their accuracy	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
Primary	Performance of students at pulp exposure prediction in the AI-based platform with and without training session based on their sensitivity	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
Primary	Performance of students at pulp exposure prediction in the AI-based platform with and without training session based on their specificity	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