Deep Learning to Summarize Findings in Dental Panoramic Radiographs
Trial Snapshot
- Phase
- Not Applicable
- Enrollment
- 1,000
- Locations
- 1
- Primary Endpoint
- Area Under Curve for Receiver Operating Characteristics of Clinical Findings
Study Overview
Brief Summary
In this work, the investigators study the application of artificial intelligence systems on dental panoramic images for dental findings. An artificial intelligence system will be learned on an publicly available panoramic image dataset, and test against the investigators' local patient cohort as external test data. The investigators hypothesize the performance would be similar, if not identical to on the public data, and that the investigators' AI system is generalizable.
Study Design
- Study Type
- Observational
- Observational Model
- Cohort
- Time Perspective
- Retrospective
Eligibility Criteria
- Ages
- 20 Years to 100 Years (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- Yes
Inclusion Criteria
- Not provided
Exclusion Criteria
- •patients under 20 or with primary teeth
- •patients with non-removable metal accessory above neck, such as tongue ring, nose ring etc.
- •patients with mandible or maxilla deformation
Outcomes
Primary Outcomes
Area Under Curve for Receiver Operating Characteristics of Clinical Findings
Time Frame: 1 day
The investigators use the AI model to infer whether a clinical finding (out of the six type of findings the investigators are interested in) is present in an imaging study from the test set. The result is compared against expert annotation and evaluated for receiver operating characteristics over the whole set. The area under curve will then be calculated and averaged across six type of findings to represent the overall efficacy of the model on detecting findings from panoramic images. From a scale of zero to one, zero is the worst this metric can be and one is the best.
Secondary Outcomes
No secondary outcomes reported