ReviewInternational journal of dentistry2026
Artificial Intelligence-Enabled Orthodontic Care for Remote and Underserved Populations: A Scoping Review of Access, Technology, and Public Health Integration.
Review in International journal of dentistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Unequal access to orthodontic care remains a major public health challenge, particularly in rural and underserved regions, recent advancements in artificial intelligence (AI) and digital orthodontics offer potential to bridge these gaps through remote diagnosis and monitoring. Aim: This scoping review aims to systematically map and categorize how AI applications in orthodontic diagnosis, treatment planning, and remote monitoring enhance access to care for underserved and remote populations while identifying specific access-related outcomes, research gaps, and policy implications for public health integration. Methods: This scoping review followed the Arksey and O'Malley framework and was reported in accordance with the preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews (PRISMA-ScR) guidelines. A comprehensive search was conducted across PubMed, Scopus, Embase, and Web of Science, supplemented with relevant gray literature. Studies published between January 2000 and September 2025 that discussed the use of AI in orthodontic diagnosis, treatment planning, appliance design, or teledentistry-based service delivery were included. Two independent reviewers performed screening and data extraction using Rayyan, and results were synthesized descriptively. Results: A total of 23 studies met the inclusion criteria. The evidence indicated that AI-assisted orthodontic systems can enhance diagnostic precision and reduce clinical workload. Remote monitoring platforms were shown to reduce in-person appointments while maintaining clinical standards and improving patient compliance. However, majority of these studies were conducted in urban or institutional environments, highlighting a significant gap in real-world longitudinal data for rural or low-resource settings. Conclusion: While AI holds transformative potential to decentralize orthodontic care, current research remains largely limited to urban settings, necessitating a shift towards real-world validation and ethical policy effort to ensure equitable delivery in underserved regions.
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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.