ArticleBioinformation2025
Marginal and internal fit of endo-crowns: AI-based evaluation.
Article in Bioinformation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Accuracy and Functional Performance of Artificial Intelligence-Based Automated Crown Design Systems: A Systematic Review and Meta-Analysis.Biomedical engineering and computational biology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The internal and marginal adaptation of endo-crown restorations fabricated using traditional and digital impression techniques is described. Artificial intelligence (AI) was used to analyze high-resolution imaging data obtained through digital scanning and micro-computed tomography. Results showed that endo-crowns produced with digital impressions exhibited superior fit compared to those made with conventional methods. AI-based analysis provided more accurate and consistent measurements than manual evaluation. Thus, we show AI's potential to enhance the precision of prosthodontic assessments.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.