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TRUVACE RECORD VERSION
record: TRV-2026-0856
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-08-23T06:03:13.454157Z
status: published
lens: g_space
sector: sports
headline: Can Artificial Intelligence Match Human Expertise in Long-Term Periodontal Prognosis? A Comparative Accuracy Study
dek: To compare the prognostic performance of an artificial intelligence (AI) model with that of experienced clinicians in predicting tooth loss over a 10-year period. An AI model trained on structured clinical and radiographic data was compared with 12 periodontists and 11 general dentists (GDs), who independently assigned prognostic scores (0-10 scale) to 300 teeth with known 10-year outcomes. AI and clinician performance were evaluated under a fixed threshold and group-specific optimal thresholds. Accuracy, sensit…
gain_title: Using the fixed threshold (score > 5 = survival), clinicians achieved higher overall accuracy than AI (75.6% periodontists, 74.9% GDs, 69.2% AI; p < 0.05), with sensitivity low and comparable across groups (14.7%-22.7%).
problem_title: (none)
trace_subject: (none)
gain_reading: Using the fixed threshold (score > 5 = survival), clinicians achieved higher overall accuracy than AI (75.6% periodontists, 74.9% GDs, 69.2% AI; p < 0.05), with sensitivity low and comparable across groups (14.7%-22.7%).
gain_evidence: (none)
problem_reading: (none)
problem_evidence: (none)
quick_read: To compare the prognostic performance of an artificial intelligence (AI) model with that of experienced clinicians in predicting tooth loss over a 10-year period. An AI model trained on structured clinical and radiographic data was compared with 12 periodontists and 11 general dentists (GDs), who independently assigned prognostic scores (0-10 scale) to 300 teeth with known 10-year outcomes.

AI and clinician performance were evaluated under a fixed threshold and group-specific optimal thresholds. Using the fixed threshold (score > 5 = survival), clinicians achieved higher overall accuracy than AI (75.6% periodontists, 74.9% GDs, 69.2% AI; p < 0.05), with sensitivity low and comparable across groups (14.7%-22.7%).
limitation: 
tag: Evidence-backed gain
key_points: To compare the prognostic performance of an artificial intelligence (AI) model with that of experienced clinicians in predicting tooth loss over a 10-year period. | An AI model trained on structured clinical and radiographic data was compared with 12 periodontists and 11 general dentists (GDs), who independently assigned prognostic scores (0-10 scale) to 300 teeth with known 10-year outcomes. | AI and clinician performance were evaluated under a fixed threshold and group-specific optimal thresholds.
rundown: To compare the prognostic performance of an artificial intelligence (AI) model with that of experienced clinicians in predicting tooth loss over a 10-year period. An AI model trained on structured clinical and radiographic data was compared with 12 periodontists and 11 general dentists (GDs), who independently assigned prognostic scores (0-10 scale) to 300 teeth with known 10-year outcomes.

AI and clinician performance were evaluated under a fixed threshold and group-specific optimal thresholds. Accuracy, sensitivity, specificity, predictive values, area under the receiver operating characteristic curve and calibration were used for comparison.
sources:
- peer_reviewed | Journal of Clinical Periodontology | https://doi.org/10.1111/jcpe.70191 | 2026-08-21
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