Assess A Smartphone App (AICaries) that uses artificial intelligence to detect dental caries in children and provide interactive oral health education: Protocol for design and usability testing (Preprint)

2021 ◽  
Author(s):  
Jin Xiao ◽  
Jiebo Luo ◽  
Oriana Ly-Mapes ◽  
Tong Tong Wu ◽  
Timothy Dye ◽  
...  

BACKGROUND Early childhood caries (ECC) is the most common chronic childhood disease, with nearly 1.8 billion new cases per year globally. 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, mHealth tools, such as smartphone application, hold great promise to achieve patient-driven early detection and risk control of ECC. OBJECTIVE This study aims to employ a community-based participatory research strategy to refine and test the usability of an artificial intelligence (AI) -powered smartphone app, AICaries, to be used by children's parents/caregivers for dental caries detection in their children. METHODS Our previous work has led to the prototype of AICaries, which offers AI-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 utilize a 2-step qualitative study design to assess the feedback and usability of the app component, app flow and whether parents can take photo 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. RESULTS The study is funded by the National Institute of Dental and Craniofacial Research, USA. This study received IRB approval and launched in August, 2021. Data collection and analysis are expected to conclude by March 2021 and June 2022, respectively. CONCLUSIONS Using AICaries, parents can use their regular smartphones to take photo 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 future clinical trial that evaluates the real-world impact of using this innovative smartphone app on early detection and prevention of ECC among low-income children.

2020 ◽  
Vol 9 (11) ◽  
pp. 3579
Author(s):  
María Prados-Privado ◽  
Javier García Villalón ◽  
Carlos Hugo Martínez-Martínez ◽  
Carlos Ivorra ◽  
Juan Carlos Prados-Frutos

Dental caries is the most prevalent dental disease worldwide, and neural networks and artificial intelligence are increasingly being used in the field of dentistry. This systematic review aims to identify the state of the art of neural networks in caries detection and diagnosis. A search was conducted in PubMed, Institute of Electrical and Electronics Engineers (IEEE) Xplore, and ScienceDirect. Data extraction was performed independently by two reviewers. The quality of the selected studies was assessed using the Cochrane Handbook tool. Thirteen studies were included. Most of the included studies employed periapical, near-infrared light transillumination, and bitewing radiography. The image databases ranged from 87 to 3000 images, with a mean of 669 images. Seven of the included studies labeled the dental caries in each image by experienced dentists. Not all of the studies detailed how caries was defined, and not all detailed the type of carious lesion detected. Each study included in this review used a different neural network and different outcome metrics. All this variability complicates the conclusions that can be made about the reliability or not of a neural network to detect and diagnose caries. A comparison between neural network and dentist results is also necessary.


2018 ◽  
Vol 4 (1) ◽  
pp. 49-57
Author(s):  
M. Lin ◽  
G. Thornton-Evans ◽  
S.O. Griffin ◽  
L. Wei ◽  
M. Junger ◽  
...  

Introduction: From 1999–2004 to 2011–2014, untreated dental caries prevalence decreased among US children aged 2 to 5 y, regardless of family income. Policies were concurrently initiated for children to increase access to preventive dental services in dental, primary, and community settings and to restorative care in dental settings. Objectives: We aimed to examine 1) whether changes in prevalence and severity of untreated and treated caries between the periods varied by family income and 2) to what degree increased past-year dental visit (PYDV) contributed to the changes. Methods: We used data for 3,822 children in the National Health and Nutrition Examination Survey 1999 to 2004 and 2011 to 2014. Caries prevalence included prevalence of untreated caries with ≥1 decayed teeth (dt) and prevalence of treated caries with ≥1 filled teeth (ft). Caries severity included number of dt and ft among those with ≥1 dt or ft. We estimated changes in caries outcomes among low- and higher-income children with models—one controlling for sociodemographics and another controlling for sociodemographics and PYDV. Significant changes ( P < 0.05) becoming insignificant after controlling for PYDV provide insight on the contribution of PYDV to changes in outcomes. Results: Prevalence of untreated caries decreased for low- and higher-income children, with a slightly larger decrease for low-income children; dt decreased only for low-income children; and estimated decreases did not vary by model. An increase in prevalence of treated caries was observed only among low-income children but became minimized and insignificant after controlling for PYDV. Similarly, after controlling for PYDV, the increase in ft among low-income children lost significance, whereas the increase among higher-income children remained. Conclusion: Untreated caries among children aged 2 to 5 y declined from 1999–2004 to 2011–2014, with larger declines among low-income children. While changes in PYDV contributed to increases in treated caries, particularly for low-income children, additional factors appear to have contributed to decreased untreated caries. Knowledge Transfer Statement: For young children, the degree and direction of changes in caries over the last decade varied by outcome measure (e.g., untreated or treated) and family poverty status. Examining the effect of increased dental utilization on changes in untreated and treated caries outcomes can help identify those policies that contribute to changes in these outcomes and highlight the potential role of the different caries assessment criteria used in dental offices versus those in a population-based survey.


2021 ◽  
Vol 15 (8) ◽  
pp. 2297-2300
Author(s):  
Faisal Izhar ◽  
M. Saleem Rana ◽  
Maha Tanvir ◽  
Shafia Hasan ◽  
Muhammad Azizullah ◽  
...  

Oral health in the nation’s evolution, especially in this globalization, an absence of illness in the population plays a key role for a fecund and well established society. Purpose: To find the prevalence of dental caries along-with the risk factors related to them in rural children of District Kasur. Study Design: Cross sectional study. Methodology: Children (n=383) were included in present study through non-probability, convenient sampling technique. Children who fulfilled the inclusion criteria were examined with the examination tools on the dental unit office in the RHC for caries risk using a pre-validated caries risk assessment checklist and Dental Caries detection form. Statistical analysis: Data analyzed by SPSS 21.0v. Results: There are 83 (22%) male and 300 (78%) females in the present study. The respondents of age 7 and over with active and smooth surface caries 383 (100%). The DMFT status for respondents with age 7-10 was 26.4% , age 11-13 was 53.5% , age 14-15 with was 18.8%. Overall dental caries risk in the participants while categorizing them on the basis of high risk i.e. 55.6% , moderate risk i.e. 42% and low risk i.e. 2.3%. Conclusion: This study concluded that caries are present in the form of tooth decay, molars, plaque, lesions, cavities, and gingivitis. The dental problems can be prevented with cleaning teeth at least twice a day with fluoride toothpaste. Key Words: Early Childhood Caries, Risk Assessment, Prevalence and Oral Hygiene.


2004 ◽  
Vol 171 (4S) ◽  
pp. 101-102
Author(s):  
Tracey L. Krupski ◽  
Arlene Fink ◽  
Lorna Kwan ◽  
Sarah Connor ◽  
Sally L. Maliski ◽  
...  

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