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Current Lit - Radiology/Imaging/CBCT correctly answered to pass
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Current Lit - Radiology/Imaging/CBCT correctly answered to pass
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Current Lit - Radiology/Imaging/CBCTDLS lesion detection accuracy was 0.93 with specificity of 0.88, positive predictive value of 0.87, and
negative predictive value of 0.93.
This Deep Learning algorithm trained in a limited CBCT environment showed
excellent results in lesion detection accuracy.
This artificial intelligence is becoming very good, and read the CBCT as well as a clinician. - correct
answer ✔✔Seltzer et al. (2020) - JOE - Artificial Intelligence for the Computer-aided Detection of
Periapical Lesions in Cone-beam Computed Tomographic Images
LOE: 5, benchtop
Periapical radiograph is inadequate in detecting resorption progress after the treatment of furcation
perforation.
When in doubt, take CBCT which is more accurate than Periapical radiographs. - correct answer
✔✔Huamán et al. (2020) - JOE - Accuracy of Conventional Periapical Radiography in Diagnosing
Furcation Repair after Perforation Treatment
LOE: 5, benchtop
Pulp necrosis was a preoperative predictor for apical periodontitis visible only in CBCT images.
Diagnosis of pulp necrosis in molars may be reasons to take CBCT. - correct answer ✔✔Jang et al. (2020)
- JOE - Clinical factors associated with apical periodontitis visible on cone-beam computed tomography
but missed with periapical radiographs: a retrospective clinical study
LOE: 4, retrospective
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