ArticleInternational journal of environmental research and public health2020
Exploring the Intersection between Social Determinants of Health and Unmet Dental Care Needs Using Deep Learning.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Educational Applications of ChatGPT in University-Based Dental Education. A Systematic Review.European journal of dental education : official journal of the Association for Dental Education in Europe · 2026Pooled it
- Classifying Delayed Dental Care Using Machine Learning: A National Health Interview Survey Analysis.International dental journal · 2026Article
- A machine learning approach to healthcare needs and barriers using the 100% Community Survey of access to SDOH services.Frontiers in public health · 2025Article
- Oral Health and Older Adults: A Narrative Review.Dentistry journal · 2024Review
- Article
- Dental health status, dentist visiting, and dental insurance of Asian immigrants in Canada.International journal for equity in health · 2023Article
- Machine Learning in Dentistry: A Scoping Review.Journal of clinical medicine · 2023Article
- Social Determinants of Health and Child Maltreatment Prevention: The Family Success Network Pilot.International journal of environmental research and public health · 2022Article
- Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis.Healthcare (Basel, Switzerland) · 2022Review
- Association Between Adverse Childhood Experiences at Age 5 Years and Healthcare Utilization at Age 9 Years.The Journal of pediatrics · 2022Article
- Gender differences in under-reporting hiring discrimination in Korea: a machine learning approach.Epidemiology and health · 2021Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The goals of this study were to develop a risk prediction model in unmet dental care needs and to explore the intersection between social determinants of health and unmet dental care needs in the United States. Data from the 2016 Medical Expenditure Panel Survey were used for this study. A chi-squared test was used to examine the difference in social determinants of health between those with and without unmet dental needs. Machine learning was used to determine top predictors of unmet dental care needs and to build a risk prediction model to identify those with unmet dental care needs. Age was the most important predictor of unmet dental care needs. Other important predictors included income, family size, educational level, unmet medical needs, and emergency room visit charges. The risk prediction model of unmet dental care needs attained an accuracy of 82.6%, sensitivity of 77.8%, specificity of 87.4%, precision of 82.9%, and area under the curve of 0.918. Social determinants of health have a strong relationship with unmet dental care needs. The application of deep learning in artificial intelligence represents a significant innovation in dentistry and enables a major advancement in our understanding of unmet dental care needs on an individual level that has never been done before. This study presents promising findings and the results are expected to be useful in risk assessment of unmet dental care needs and can guide targeted intervention in the general population of the United States.
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Registered trials
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