The purpose of this study is to assess the impact of artificial intelligence on proximal caries detection and subsequent treatment decisions of early learners and compare those with outcomes of experienced learners.
Provide informed consent
Willing to comply with all study procedures and be available for the duration of the study
Dental student in second, third, or fourth year of dental school at University of Michigan School of Dentistry
Provide informed consent
Dental students who do not have previous experience with caries detection (such as first year dental students)
Residents that do not have frequent exposure to caries detection, such as orthodontic, periodontic, oral surgery graduate residents.
Crossover
Review of Radiograph Images
Other interventionParticipants will be asked to attend two visits and view a randomized series of dental radiographs (10 at each visit). Participants will answer a set of questions for each image reviewed. Some of the radiographs will have an Artificial Intelligence enhancement and some will not. Participants will be asked to return within about one week of the first visit to view the second set of x-rays and answer the survey questions.
Lesion severity
Levels for this outcome will be sound, outer enamel, inner enamel/outer dentin, inner dentin.
Diagnostic accuracy
Specificity
Overall sensitivity
Intervention
(levels for this outcome will be none, non-restorative, restorative)
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University of Michigan
Lead sponsor
Delta Dental Plan of Michigan
Collaborator
