ArticleInternational dental journal2023
Accuracy of Artificial Intelligence-Based Photographic Detection of Gingivitis.
Article in International dental journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07187453 (Improving Gum Health Among Older Adults in Hong Kong Through Artificial Intelligence-Based Mobile Health for Personalized Oral Hygiene Instruction), which is not on this map. Cited by 41 papers, 3 of them syntheses that pooled it.
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.
Improving Gum Health Among Older Adults in Hong Kong Through Artificial Intelligence-Based Mobile Health for Personalized Oral Hygiene Instruction
Who cites it
41 citing papers in PubMed, 3 syntheses or guidelines pooled it, 70 citations in OpenAlex.
- Deep Learning for Detecting Dental Plaque and Gingivitis From Oral Photographs: A Systematic Review.Community dentistry and oral epidemiology · 2025Pooled it
- Development of Artificial Intelligence Models for Tooth Numbering and Detection: A Systematic Review.International dental journal · 2024Pooled it
- Self-monitoring of Oral Health Using Smartphone Selfie Powered by Artificial Intelligence: Implications for Preventive Dentistry.Oral health & preventive dentistry · 2024Pooled it
- Reimagining Dental Education: Integrating Digital Technologies for a Global, Digitally Native Generation-A Perspective.European journal of dentistry · 2026Article
- Artificial Intelligence in Gingival Recession Assessment and Treatment Planning: A Scoping Review.Journal of clinical medicine · 2026Review
- Innovations using digital technologies for periodontal diagnosis and prognosis: a narrative review.Acta odontologica Scandinavica · 2026Review
- Performance of Large Language Models in Oral Health Consultations and the Consistency of the 'AI-as-a-Judge' Framework.International dental journal · 2026Article
- Evaluating the Artificial Intelligence Driven Monitoring System Notifications: Clear Aligner and Oral Hygiene Perspectives.Orthodontics & craniofacial research · 2026Article
- Beyond the Drill: Can Digital Gadgets Redefine the Future of Dental Education?European journal of dental education : official journal of the Association for Dental Education in Europe · 2026Article
- Comparative evaluation of artificial intelligence language models on knowledge of dental antibiotic use.BMC oral health · 2026Article
- OralSegNet: An Approach to Early Detection of Oral Disease Using Transfer Learning.Oral diseases · 2026Article
- AI-enabled predictive, preventive and personalised oral health management: a lightweight patient-centred model for automated assessment of dental plaque and gingival inflammation.The EPMA journal · 2026Article
- Digital Dentistry in Clinical Practice: A Scoping Review of Current Capabilities and Future Directions.International dental journal · 2026Article
- A Multimodal Large Language Model Framework for Clinical Subtyping and Malignant Transformation Risk Prediction in Oral Lichen Planus: A Paired Comparison With Expert Clinicians.International dental journal · 2026Article
- Dental Crowding Categorization Network (DCC-Net): Explainable deep learning system for automatic categorization of dental crowding on intraoral photographs.Korean journal of orthodontics · 2026Article
- Editorial: VR-haptic technologies and their applications in dental education.Frontiers in oral health · 2026Article
- Accuracy of artificial intelligence applications in periodontics: a thematic narrative review.Frontiers in dental medicine · 2026Review
- A deep learning approach to predict the results of root coverage procedures based on intraoral photographs: a retrospective study.BMC oral health · 2025Article
- [Applications and perspectives of artificial intelligence in periodontology].Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology · 2025Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesGingivitis is one of the most prevalent plaque-initiated dental diseases globally. It is challenging to maintain satisfactory plaque control without continuous professional advice. Artificial intelligence may be used to provide automated visual plaque control advice based on intraoral photographs.
methodsFrontal view intraoral photographs fulfilling selection criteria were collected. Along the gingival margin, the gingival conditions of individual sites were labelled as healthy, diseased, or questionable. Photographs were randomly assigned as training or validation datasets. Training datasets were input into a novel artificial intelligence system and its accuracy in detection of gingivitis including sensitivity, specificity, and mean intersection-over-union were analysed using validation dataset. The accuracy was reported according to STARD-2015 statement.
resultsA total of 567 intraoral photographs were collected and labelled, of which 80% were used for training and 20% for validation. Regarding training datasets, there were total 113,745,208 pixels with 9,270,413; 5,711,027; and 4,596,612 pixels were labelled as healthy, diseased, and questionable respectively. Regarding validation datasets, there were 28,319,607 pixels with 1,732,031; 1,866,104; and 1,116,493 pixels were labelled as healthy, diseased, and questionable, respectively. AI correctly predicted 1,114,623 healthy and 1,183,718 diseased pixels with sensitivity of 0.92 and specificity of 0.94. The mean intersection-over-union of the system was 0.60 and above the commonly accepted threshold of 0.50.
conclusionsArtificial intelligence could identify specific sites with and without gingival inflammation, with high sensitivity and high specificity that are on par with visual examination by human dentist. This system may be used for monitoring of the effectiveness of patients' plaque control.
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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.