ArticleFrontiers in oral health2025
Artificial intelligence-produced radiographic enhancements in dental clinical care: provider and patient perspectives.
Article in Frontiers in oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed.
- Innovations using digital technologies for periodontal diagnosis and prognosis: a narrative review.Acta odontologica Scandinavica · 2026Review
- Evaluation of the diagnostic reliability of an AI prototype in detecting clinical features from dental photographs-original research.Frontiers in dental medicine · 2026Article
- U-Net-Based Deep Learning for Simultaneous Segmentation and Agenesis Detection of Primary and Permanent Teeth in Panoramic Radiographs.Diagnostics (Basel, Switzerland) · 2025Article
- Supernumerary molars' prevalence in a Romanian population sample and their potential value in forensic investigation.Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologieArticle
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Artificial intelligence (AI)-based software can be used with dental radiographs to facilitate dental providers' diagnoses and to educate patients about their oral health conditions. The goal of this study was to survey dental providers and patients about the use of AI-enhanced radiographs in the diagnostic and patient education processes. Methods: Within their Community Collaborative Practice model, Apple Tree Dental in Minnesota implemented the use of an AI software platform that annotates carious lesions and periodontal measurements on dental radiographs. Before and after implementation of this software, providers (dentists, dental hygienists, dental therapists, and dental assistants) were surveyed about what benefits and challenges they anticipated and experienced in using the AI software. A small-scale study of patients who viewed AI-generated annotations on their own radiographs examined patient perspectives on the use of this software. Results: Dental therapists reported using the software most often, with 57.2% using the software at least 50% of their clinical time; 79% of dental assistants reported using the software 25% of the time or less. While the majority of providers ( Discussion: While provider and patient perceptions of the use of AI software in dental care were positive overall, attitudes among providers were mixed regarding its effectiveness in diagnosing dental disease and improving work efficiency. More research is needed to determine whether use of AI software in clinical dental practice produces changes in treatment recommendations by providers or in patient adherence to these recommendations.
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