Impact of Training Dental Students for an AI-Based Platform

NCT ID: NCT05912361

Last Updated: 2024-01-08

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 20 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2023-08-20
• Study Completion Date: 2024-01-01

Brief 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

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: OTHER
• Blinding Strategy: DOUBLE

Study Groups

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.

Group Type: EXPERIMENTAL

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

Intervention Type: 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.

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.

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

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.

Intervention Type: BEHAVIORAL

Eligibility Criteria

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

• Minimum Eligible Age: 20 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

University of Copenhagen

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

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

Copenhagen, , Denmark

Countries

Denmark

References

Ramezanzade S, Dascalu TL, Bakhshandeh A, Uribe SE, Ibragimov B, Bjorndal L. The Impact of Training Dental Students to Use an Artificial Intelligence-Based Platform for Pulp Exposure Prediction Prior to Deep Caries Excavation: A Proof-of-Concept Randomised Controlled Trial. Int Endod J. 2025 Oct 10. doi: 10.1111/iej.70046. Online ahead of print.

Reference Type: DERIVED

PMID: 41074395 (View on PubMed)

Other Identifiers

504-0342/22-5000

Identifier Type: -

Identifier Source: org_study_id