ArticleJMIR research protocols2021
Assessing a Smartphone App (AICaries) That Uses Artificial Intelligence to Detect Dental Caries in Children and Provides Interactive Oral Health Education: Protocol for a Design and Usability Testing Study.
Article in JMIR research protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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Who cites it
19 citing papers in PubMed, 41 citations in OpenAlex.
- Using patients' oral photographs for oral hygiene motivation promotes periodontal health: a prospective randomized controlled trial.BMC oral health · 2024Trial
- Effect of a Personalized Mobile Health Intervention Using Artificial Intelligence (the WARIFA App) Versus a Nonpersonalized Intervention on User-Defined Objectives, Healthy Lifestyles, and Management of Type 1 Diabetes (T1D): Protocol for a Randomized Controlled Trial.JMIR research protocols · 2026Article
- Mobile Imaging-Based Machine Learning for Dental Caries, Sealants, and Fluorosis: Protocol for a Cross-Sectional Model Development and Validation Study.JMIR research protocols · 2026Article
- Exploring the impact of artificial intelligence on dental education: Benefits, challenges, and future directions - A systematic review of the literature.Journal of education and health promotion · 2026Review
- Artificial intelligence and oral photography: an approach to the epidemiology of dental caries.Revista de saude publica · 2026Article
- AI-Based Intraoral Videography for Automated Dental Inspection and Charting in Children With Mixed Dentition.International journal of telemedicine and applications · 2026Article
- Evaluating Maternal Accuracy in Smartphone-Based Tele-Dentistry for Early Childhood Caries Detection.Clinical and experimental dental research · 2025Article
- Reliability of teledentistry mobile photos versus conventional clinical examination for dental caries diagnosis on occlusal surfaces in a group of school children: a diagnostic accuracy study.BMC oral health · 2025Observational
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- Validity and reliability of a smartphone-based photographic method for detection of dental caries in adults for use in teledentistry.Frontiers in oral health · 2025Article
- The role of artificial intelligence in diagnosing pediatric dental disorders-a narrative review.Frontiers in dental medicine · 2025Review
- Tech Bytes-Harnessing Artificial Intelligence for Pediatric Oral Health: A Scoping Review.International journal of clinical pediatric dentistry · 2024Article
- Time Efficiency, Reliability, and User Satisfaction of the Tooth Memo App for Recording Oral Health Information: Cross-Sectional Questionnaire Study.JMIR formative research · 2024Article
- Application of Artificial Intelligence in Clinical Dentistry, a Comprehensive Review of Literature.Journal of dentistry (Shiraz, Iran) · 2023Review
- Acceptance and Usability of an Innovative mDentistry eHygiene Model Amid the COVID-19 Pandemic Within the US National Dental Practice-Based Research Network: Mixed Methods Study.JMIR human factors · 2023Article
- COVID-19 Related Information on Pediatric Dental Care including the Use of Teledentistry: A Narrative Review.Children (Basel, Switzerland) · 2022Review
- Artificial intelligence-powered smartphone application, AICaries, improves at-home dental caries screening in children: Moderated and unmoderated usability test.PLOS digital health · 2022Article
- Assessment of an Innovative Mobile Dentistry eHygiene Model Amid the COVID-19 Pandemic in the National Dental Practice-Based Research Network: Protocol for Design, Implementation, and Usability Testing.JMIR research protocols · 2021Article
- Review
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundEarly childhood caries (ECC) is the most common chronic childhood disease, with nearly 1.8 billion new cases per year worldwide. ECC afflicts approximately 55% of low-income and minority US preschool children, resulting in harmful short- and long-term effects on health and quality of life. Clinical evidence shows that caries is reversible if detected and addressed in its early stages. However, many low-income US children often have poor access to pediatric dental services. In this underserved group, dental caries is often diagnosed at a late stage when extensive restorative treatment is needed. With more than 85% of lower-income Americans owning a smartphone, mobile health tools such as smartphone apps hold promise in achieving patient-driven early detection and risk control of ECC.
objectiveThis study aims to use a community-based participatory research strategy to refine and test the usability of an artificial intelligence-powered smartphone app, AICaries, to be used by children's parents/caregivers for dental caries detection in their children.
methodsOur previous work has led to the prototype of AICaries, which offers artificial intelligence-powered caries detection using photos of children's teeth taken by the parents' smartphones, interactive caries risk assessment, and personalized education on reducing children's ECC risk. This AICaries study will use a two-step qualitative study design to assess the feedback and usability of the app component and app flow, and whether parents can take photos of children's teeth on their own. Specifically, in step 1, we will conduct individual usability tests among 10 pairs of end users (parents with young children) to facilitate app module modification and fine-tuning using think aloud and instant data analysis strategies. In step 2, we will conduct unmoderated field testing for app feasibility and acceptability among 32 pairs of parents with their young children to assess the usability and acceptability of AICaries, including assessing the number/quality of teeth images taken by the parents for their children and parents' satisfaction.
resultsThe study is funded by the National Institute of Dental and Craniofacial Research, United States. This study received institutional review board approval and launched in August 2021. Data collection and analysis are expected to conclude by March 2022 and June 2022, respectively.
conclusionsUsing AICaries, parents can use their regular smartphones to take photos of their children's teeth and detect ECC aided by AICaries so that they can actively seek treatment for their children at an early and reversible stage of ECC. Using AICaries, parents can also obtain essential knowledge on reducing their children's caries risk. Data from this study will support a future clinical trial that evaluates the real-world impact of using this smartphone app on early detection and prevention of ECC among low-income children. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/32921.
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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.