aceExploratory machine learning-based early post-treatment assessment of willingness to reuse rubber dam isolation after microscopic root canal treatment
ObjectiveTo explore factors associated with willingness to reuse rubber dam isolation after microscopic root canal treatment and develop an exploratory machine learning-based early post-treatment assessment model.MethodsThis retrospective cross-sectional study included 306 patients who underwent microscopic root canal treatment with rubber dam isolation from May 2025 to November 2025. The outcome was the willingness to reuse rubber dam isolation at the 1-week follow-up. Forty-seven newly enrolled patients were r…
An exploratory Light Gradient Boosting Machine model predicted 1-week willingness to reuse rubber dam isolation after microscopic root canal treatment with AUC 0.939 in held-out test and 0.983 in temporal validation.
Model performance dropped when satisfaction was excluded and estimates from the small same-center temporal validation cohort with only 14 unwilling patients were considered preliminary and potentially imprecise.
Temporal validation was based on only 47 patients including 14 unwilling to reuse, making performance estimates preliminary and imprecise, with prospective multicenter validation still required.
Evidence
- Peer-reviewedJournal of International Medical Research2026-08-01
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Truvace Impact Record TRV-2026-0631, v1: “Exploratory machine learning-based early post-treatment assessment of willingness to reuse rubber dam isolation after microscopic root canal treatment.” Truvace, 2026-08-03. /record/TRV-2026-0631 (accessed at citation time). sha256 eba1b0a06046e03f…
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