Tooth loss is often accepted as a natural part of aging, but what if there was a way to better identify those most susceptible without the need for a dental exam?
New research led by investigators at Harvard School of Dental Medicine (HSDM) suggests that machine learning tools can help identify those at greatest risk for tooth loss and refer them for further dental assessment in an effort to ensure early interventions to avert or delay the condition.
The study, published June 18 in PLOS ONE, compared five algorithms using a different combination of variables to screen for risk.... Read more about Predicting Tooth Loss: Machine-Learning Algorithms May Help Identify Those at Risk