Dental Diseases, Dentist-Patient Relations, Digital, Radiography
Conditions
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.
Interventions
RADIATIONDental Panoramic Radiographs
Exposure to dental panoramic radiographs
Sponsors
National Taiwan University Hospital
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
20 Years to 100 Years
Healthy volunteers
Yes
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Area Under Curve for Receiver Operating Characteristics of Clinical Findings | 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. |
Countries
Taiwan
Outcome results
None listed