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OpenTrials
Completed

NCT Number: NCT05912361

Impact of Training Dental Students for an AI-Based Platform

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.

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Key information

Conditions

Artificial Intelligence Education

Age range

20 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

University of Copenhagen Department of Odontology Cariology and Endodontics Section for Clinical Oral Microbiology

Copenhagen, 2200, Denmark

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

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

Behavioral

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.

Primary outcomes

  1. 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.

  2. 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).

  3. 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).

Sponsors and collaborators

Lead sponsor

University of Copenhagen

Other

Registry information

Official study 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

Important dates

Study start
2023
Primary completion
2023
Study completion
2024
First posted
Jun 22, 2023
Registry last updated
Jan 8, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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