ArticleBMC oral health2026
Learning curve of autonomous computer-assisted implant surgery systems for postgraduate dental trainees: an in vitro study.
Article in BMC oral health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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Who cites it
2 citing papers in PubMed.
- AI-Assisted Dual-Template Workflow in Tooth Autotransplantation: A Promising Step Toward Precision Dentistry.International dental journal · 2026Article
- Robot-Assisted Dentistry: What the Evidence Supports and Which Outcomes Are Still Missing.Cureus · 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
Abstract
objectivesThis study investigated the accuracy and learning curve of dental postgraduate trainees in robot-assisted implant surgery (r-CAIS) and examined the characteristics of learning curve. MATERIALS AND
methodsAfter receiving comprehensive training, eleven dental trainees used r-CAIS to place three implants, 3 trials per day over four experimental days, with each experimental day occurring every 72 h. Trueness was assessed by comparing postoperative model scans with preoperative planning. The total time was recorded during the experiment and subsequently categorized into preparation and surgery times.
resultsThe average deviations for platform, apex, and angular were 0.91 ± 0.39 mm, 0.93 ± 0.38 mm, and 1.38 ± 0.61°, respectively. The mean total time, preparation time, and surgery time were 954.36 ± 222.69 s, 321.36 ± 119.30 s, and 632.53 ± 140.30 s, respectively. Analysis indicated that there were no statistically significant differences in trueness between different experimental days and trials for platform, apex, and angular (p-values: Day: 0.0924, 0.2735, 0.3223; Trial: 0.6647, 0.7873, 0.5270). However, all time measures (total, preparation, and surgery time) showed significant reductions as days and trials increased (p-values < 0.0001 for all). Additionally, there was a significant interaction between days and trials for surgery time (p = 0.0123). Normality tests revealed that the trueness data and surgery time were not normally distributed on day 1, but conformed to a normal distribution on the rest days.
conclusionThe results demonstrated stability in trueness during the learning phase of r-CAIS, although there could still be a learning curve in terms of time metrics. Additionally, the accumulation of experience may exert varying influences during the preparation and surgical phases. CLINICAL SIGNIFICANCE: The r-CAIS can enable dental trainees to achieve high trueness during their initial exposure to surgical procedures. Understanding the differing learning processes associated with various r-CAIS procedures can help develop more effective training programs and promote the broader clinical applications of r-CAIS.
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