Dental caries, chronic apical periodontitis K02 K04.5
Conditions
Interventions
Group 1: This observational, multicenter, cross-sectional benchmarking study uses retrospectively collected, de-identified bitewing, periapical, and panoramic radiographs from multiple international d
Sponsors
LMU Klinikum, Poliklinik für Zahnerhaltung, Parodontologie und digitale Zahnmedizin
Eligibility
Sex/Gender
All
Age
18 Years to No maximum
Inclusion criteria
Inclusion criteria: De-identified bitewing, periapical and panoramic radiographs in high resolution (JPEG/PNG format).
Exclusion criteria
Exclusion criteria: Radiographs with significant artifacts obscuring diagnostic regions.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Diagnostic performance of selected commercial, web-based AI diagnostic tools in detecting caries and periapical radiolucencies on retrospectively collected de-identified bitewing, periapical, and panoramic radiographs, using calibrated expert annotations as the reference standard. Performance will be assessed by accuracy, sensitivity, specificity, precision, and F1 score. | — |
Secondary
| Measure | Time frame |
|---|---|
| The study will also examine the potential influence of patient demographic characteristics, including age and sex, on AI diagnostic performance. | — |
Countries
Czechia, France, Malaysia, South Korea, United States
Contacts
Public ContactFalk Schwendicke
LMU Klinikum, Poliklinik für Zahnerhaltung, Parodontologie und digitale Zahnmedizin
Outcome results
None listed