Impact of Training Dental Students for an AI-Based Platform

Status Completed

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.

Clinical Trial Description

n/a

Study Design

Related Conditions & MeSH terms

Clinical Trial Details

NCT number	NCT05912361
Study type	Interventional
Source	University of Copenhagen
Contact
Status	Completed
Phase	N/A
Start date	August 20, 2023
Completion date	January 1, 2024

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