ReviewDigital health
Impact of artificial intelligence-based digital smile design on patient and clinician satisfaction and facial esthetic outcomes: A systematic review and meta-analysis.
Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
5 citing papers in PubMed.
- Mapping the Influence of Artificial Intelligence in Prosthodontics: A Scoping Review of the Current Trends and Challenges.Dentistry journal · 2026Review
- Human perception of AI-generated post-treatment orthodontic facial images: factors associated with misclassification.Clinical oral investigations · 2026Article
- Article
- Present and Future of the Use of Artificial Intelligence in Orthodontics.Bioengineering (Basel, Switzerland) · 2026Review
- Exploring Medical Information Needs and Accessibility in Swedish Dental Care by Analysis of Documentation Workflows and Electronic Dental Records in Dalarna: Sociotechnical Qualitative Study.JMIR human factors · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: This study aimed to evaluate the influence of artificial intelligence (AI)-generated Digital Smile Design (DSD) on patients and clinician satisfaction, and overall aesthetic outcomes. Methods: A comprehensive search of PubMed, Scopus, Cochrane Library, ScienceDirect, and Google Scholar was conducted to identify studies (2004-2024) evaluating AI-based DSD. Eligible studies reported patient/clinician satisfaction or facial esthetic outcomes. Data were extracted on study characteristics, participant demographics, DSD type, and outcome measures. A meta-analysis of satisfaction prevalence was performed using Jamovi with a random-effects model. Methodological quality was assessed using the ROBINS-I tool, and publication bias was evaluated via rank correlation, fail-safe N, and regression tests for funnel plot asymmetry. Results: Seven studies were included after screening 387 records. AI-based tools (e.g. SmileCloud, REBEL, and Invisalign SmileView) improved esthetic outcomes, enhancing smile symmetry, lip arcs, and incisal edge visibility. Key predictors of success included philtrum height and buccal corridor. The meta-analysis showed a pooled satisfaction prevalence of 58% (95% CI: 0.30-0.86, Conclusion: These findings suggest that AI-generated DSD provides significant facial esthetic outcomes. However, future studies should explore the long-term sustainability of these outcomes and the cost-effectiveness of AI-based dental treatments.
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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.