The Impact of Artificial Intelligence on Dentists' Decision-Making Process During Caries Detection

ConditionsArtificial Intelligence (AI) in Diagnosis Artificial Intelligence Supported Image Reviewing

Trial statusNot yet recruiting

Trial phaseNot applicable

Trial typeInterventional

Biological sexAll

AgeNot listed

SponsorRadboud University Medical Center

About this trial

This study aims to evaluate the influence of artificial intelligence (AI) on the decision-making process for intervention after caries lesion detection. Participants will be dentists working in the Netherlands randomly divided into two groups. Dentists will be divided into two groups and receive a set of bitewing radiographs, which first will be evaluated with or without AI support according to their group. Participants will examine caries lesions on the radiographs and formulate treatment plans accordingly. Then, after a wash-out period of one month, the same radiographs, but in the opposite condition of AI support and again formulate treatment suggestions according to the present caries lesions.

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

Graduated, practising dentists.

At least three years of experience

Disqualifiers

Retired dentists.

Specialized practitioners (e.g., orthodontists and oral surgeons) if their typical practice does not involve routine caries diagnostics and treatment planning.

Trial design

Design model

Crossover

Treatments tested in this trial

Artificial intelligence in diagnosis
Diagnostic test
AI-based diagnostic programs have proved to enhance diagnostic performance, however research on its effects on treatment decisions is scarce. In contrast to other studies focusing on AI's accuracy or the resulting increase in dentists' accuracy, this study aims to investigate the differences in dentists' treatment recommendations when supported by AI versus when they are not during caries detection.

Treatment groups

25 Participants

are divided into 2 treatment groups

Group A: Phase 1: Caries detection without AI, Phase 2: Caries detection with AIActive comparator 1 intervention

Group B: Phase 1: Caries detection with AI, Phase 2: Caries detection without AIActive comparator 1 intervention

Trial outcomes

Primary outcomes

Treatment decisions: Compare the treatment recommendations of dentists for caries lesions detected with and without AI support.

The given options will be "no treatment", "non-invasive treatment" (fluoride varnish, polishing, sealing), and "restoration". Participants' answers will be compared to a reference standard.

Time frame

Each participant will be assessed over a period of up to 2 months (includes both evaluation phases and washout period)

Secondary outcomes

Diagnostic Accuracy in Caries Detection

RA0: No radiolucency - No visible caries. RA1: Radiolucency confined to the outer half of enamel - Enamel caries. RA2: Radiolucency extending to the inner half of enamel but not reaching dentin - Moderate enamel caries. RA3: Radiolucency extending into the outer third of dentin - Dentin caries. RA4: Radiolucency extending into the middle of dentin - Advanced dentin caries. RA5: Radiolucency extending into the inner third of dentin - Severe dentin caries. Participants' answers will be compared to a reference standard.

Time frame

Each participant will be assessed over a period of up to 2 months (includes both evaluation phases and washout period)

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

Radboud University Medical Center

Lead sponsor

Prime Dental Alliance Eindhoven

Collaborator

Source ClinicalTrials.gov

This trial is not recruiting at the moment. You can still explore other options: