Abstract
Background: The application of AI algorithms for the detection of the mandibular canal in Cone Beam Computed Tomography (CBCT) holds immense promise in dentistry. Aim: This review aimed to identify the semi and fully automated algorithm to localize the mandibular canal. An extensive search was conducted and, out of which 12 articles are considered for review. The result revealed using various AI algorithms achieved better accuracy in localizing the mandibular canal with reporting sensitivity and specificity above 90 %. In conclusion, it is noted that the application of AI algorithms in dentistry can provide significant benefits like improving the accuracy of reporting.
| Original language | English |
|---|---|
| Article number | 101760 |
| Journal | Clinical Epidemiology and Global Health |
| Volume | 29 |
| DOIs | |
| Publication status | Published - 01-09-2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Epidemiology
- Public Health, Environmental and Occupational Health
- Microbiology (medical)
- Infectious Diseases
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