Penn researchers use machine learning to identify tooth decay risk factors
Penn researchers use machine learning to identify tooth decay risk factors
https://www.thedp.com/article/2026/02/penn-dental-tooth-decay-ai-machine-learning
Publish Date: 2026-02-04 00:06:00
Source Domain: www.thedp.com
- Penn researchers developed an AI-powered process for identifying risk factors associated with tooth decay using machine learning from the National Health and Nutrition Examination Survey (NHANES).
- Led by Orthodontics professor Michel Koo and Biostatistics and Epidemiology professor Jason Moore, the study revealed previously unrecognized patterns linking dental health with systemic, nutritional, and environmental factors.
- The study highlighted significant dental health issues among children under 5, who showed iron and vitamin D deficiencies, and older adults over 65.
- It indicated that tooth decay could be a “sentinel marker” of underlying systemic health problems and associated high-sugar-content foods with decay, including apple juice and energy drinks.
- Researchers also found potential links between sleep and tooth decay, calling for further investigation on this subject.
