Deep Learning to Summarize Findings in Dental Panoramic Radiographs

National Taiwan University Hospital1,000 enrolled

Overview

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 Type

OBSERVATIONAL

Enrollment

1,000

Conditions

Radiography Digital Dental Diseases Dentist-Patient Relations

Interventions

Dental Panoramic Radiographs

Eligibility

Sex: ALLMin age: 20 YearsMax age: 100 YearsHealthy volunteers:

Medical Language ↔ Plain English

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

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.

Time frame: 1 day

Data from ClinicalTrials.gov

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