AI-enabled orthodontic diagnosis and remote monitoring to improve access for remote and underserved populations
Source article: Artificial Intelligence-Enabled Orthodontic Care for Remote and Underserved Populations: A Scoping Review of Access, Technology, and Public Health Integration
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 identi…
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This scoping review examined 23 studies published between January 2000 and September 2025 on AI in orthodontic diagnosis, treatment planning, appliance design, and teledentistry. It found AI-assisted systems can improve diagnostic precision and reduce clinical workload, and that remote monitoring platforms can cut in-person appointments while maintaining standards and improving compliance.
The findings matter for public health because orthodontic access remains unequal in rural and underserved regions, and AI-enabled remote care could help decentralize services. Uncertainty remains because most included studies were from urban or institutional settings, so effectiveness, compliance, and equity impacts in low-resource, real-world rural contexts are not yet established and will require longitudinal validation and policy safeguards.
- Scoping review of 23 studies from January 2000 to September 2025 across PubMed, Scopus, Embase, and Web of Science found AI can enhance diagnostic precision and reduce clinical workload.
- Remote monitoring was shown to reduce in-person appointments while maintaining clinical standards and improving compliance.
- Most evidence comes from urban or institutional environments, leaving a gap in longitudinal real-world data for rural or low-resource settings.
AI-assisted orthodontic systems and remote monitoring platforms reduced in-person appointments while maintaining clinical standards and improving patient compliance in included studies.
Most studies of AI-enabled orthodontic care were conducted in urban or institutional environments, leaving a significant gap in real-world longitudinal data for rural or low-resource settings where access remains a major challenge.
The rundown
The review followed the Arksey and O'Malley framework and PRISMA-ScR guidelines, with screening and extraction by two independent reviewers using Rayyan and synthesis of 23 eligible studies including gray literature.
Authors mapped AI uses across diagnosis, treatment planning, appliance design, and teledentistry-based delivery, noting potential to decentralize care but calling for ethical policy efforts and real-world validation to ensure equitable delivery.
Evidence base is concentrated in urban or institutional environments with limited longitudinal real-world validation in rural or low-resource settings.
Sources
- Peer-reviewedInternational Journal of Dentistry2026-09-12
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