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Impact of Training Dental Students for an AI-Based Platform

NCT05912361 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 20

Last updated 2024-01-08

No results posted yet for this study

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.

Conditions

  • Artificial Intelligence
  • Education

Interventions

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.

Sponsors & Collaborators

  • University of Copenhagen

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
OTHER
Masking
DOUBLE
Model
PARALLEL

Eligibility

Min Age
20 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2023-08-20
Primary Completion
2023-12-20
Completion
2024-01-01

Countries

  • Denmark

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05912361 on ClinicalTrials.gov