ArticleInternational dental journal2025
Comparison of the Efficacy of Artificial Intelligence-Powered Software in Crown Design: An In Vitro Study.
Article in International dental journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07432165 (Accuracy Assessment of Artificial Intelligence Versus Conventional Digital Design for Fixed Dental Prosthesis), which is not on this map. Cited by 13 papers, 2 of them syntheses that pooled it.
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.
Accuracy Assessment of Artificial Intelligence Versus Conventional Digital Design for Fixed Dental Prosthesis: (An Invitro Study)
Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The application of artificial intelligence in the field of dental restoration for designing dental crowns: a meta-analysis.BMC oral health · 2026Pooled it
- A Systematic Review of the Accuracy of Crowns Designed Using Artificial Intelligence Versus CAD/CAM and Traditional Methods.Medicina (Kaunas, Lithuania) · 2026Pooled it
- Influence of conventional and AI-assisted dental CAD software and 3D printing technology on the intaglio surface trueness of interim crowns.The journal of advanced prosthodontics · 2026Article
- Artificial Intelligence (AI) in Computer-Aided Design (CAD): How AI Is Redefining Dental CAD.Cureus · 2026Review
- AI-driven automation of occlusal surface design in digital prosthodontics: a clinically validated workflow.BMC oral health · 2026Article
- Artificial Intelligence-Driven Automated Design of Anterior and Posterior Crowns Under Diverse Occlusal Scenarios.Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.] · 2026Article
- Accuracy and Functional Performance of Artificial Intelligence-Based Automated Crown Design Systems: A Systematic Review and Meta-Analysis.Biomedical engineering and computational biology · 2026Review
- Application of artificial intelligence in oral health management: challenges and opportunities.Frontiers in medicine · 2026Review
- Future of dental education: digitalization, career outlook, and perspectives of dental students and early-career dentists.BMC medical education · 2025Article
- Application and development of artificial intelligence and immersive technologies in dental education: a scoping review.BMC medical education · 2025Article
- Feasibility and accuracy assessment of AI-driven incisor restoration using 3D point cloud data.Clinical oral investigations · 2025Article
- Morphological comparison between artificial intelligence-driven and manual CAD design in single tooth restoration: a preliminary study.BMC oral health · 2025Article
- Long-Term Predictive Modelling of the Craniofacial Complex Using Machine Learning on 2D Cephalometric Radiographs.International dental journal · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
INTRODUCTION AND
aimsArtificial intelligence (AI) has been adopted in the field of dental restoration. This study aimed to evaluate the time efficiency and morphological accuracy of crowns designed by two AI-powered software programs in comparison with conventional computer-aided design software.
methodsA total of 33 clinically adapted posterior crowns were involved in the standard group. AI Automate (AA) and AI Dentbird Crown (AD) used two AI-powered design software programs, while the computer-aided experienced and computer-aided novice employed the Exocad DentalCAD software. Time efficiency between the AI-powered groups and computer-aided groups was evaluated by assessing the elapsed time. Morphological accuracy was assessed by means of three-dimensional geometric calculations, with the root-mean-square error compared against the standard group. Statistical analysis was conducted via the Kruskal-Wallis test (α = 0.05).
resultsThe time efficiency of the AI-powered groups was significantly higher than that of the computer-aided groups (P < .01). Moreover, the working time for both AA and AD groups was only one-quarter of that for the computer-aided novice group. Four groups significantly differed in morphological accuracy for occlusal and distal surfaces (P < .05). The AD group performed lower accuracy than the other three groups on the occlusal surfaces (P < .001) and the computer-aided experienced group was superior to the AA group in terms of accuracy on the distal surfaces (P = .029). However, morphological accuracy showed no significant difference among the four groups for mesial surfaces and margin lines (P > .05).
conclusionAI-powered software enhanced the efficiency of crown design but failed to excel at morphological accuracy compared with experienced technicians using computer-aided software. AI-powered software requires further research and extensive deep learning to improve the morphological accuracy and stability of the crown design.
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