Researchers have developed an artificial intelligence (AI) model to predict which patients are at high risk of developing caries.
In a collaboration between New York University (NYU) and the Federal University of Santa Maria, data from almost 24,000 patients in Brazil was used to create a machine learning model to predict caries risk and severity by age group. Using an AI algorithm allowed researchers to analyse large, complex datasets in order to find patterns that would be difficult to pinpoint otherwise.
The strongest risk signals were wealth and household density. Non-white groups had higher caries risk across ages, while private dental insurance and a recent dental visit were protective factors.
Water fluoridation was also a strong predictor: 62.5% of 12-year-olds without fluoridated water had cavities, versus 35.5% with fluoridated systems.
‘The emergence of AI offers a transformative opportunity for public health surveillance and risk stratification, including addressing the global burden of cavities,’ said Fernando Neves Hugo, chair of the Department of Epidemiology and Health Promotion at NYU College of Dentistry. ‘These are powerful tools that could be helpful for targeting resources and delivering preventive care to specific groups that will benefit the most.’
How does AI predict caries risk?
The researchers found that AI could accurately predict cavity risk and severity by age group by evaluating the relative contributions of the different factors.
Hugo continued: ‘Our machine learning approach acts as a high-resolution sensor that identifies individuals whose profiles signal a heightened risk that would otherwise be invisible within community averages.’
Sourced from Brazil’s 2023 national oral-health survey, the researchers note that the same models might be applicable to other middle-income countries but local access would likely shift the factors that lead to caries development in other countries.
Hugo and his colleagues are planning to conduct similar research using US data from the National Health and Nutrition Examination Survey.
He added: ‘When we think about public health and preventive interventions, we need to be accountable to society and make the best use of the resources we have. A more targeted approach helps us optimise resources – essentially, getting more bang for our buck.’
The research was published in Caries Research in October.
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