Fairness of Machine Learning Algorithms for Predicting Foregone Preventive Dental Care for Adults

This is the authors' abstract. We don't add key points for this paper.

Findings of this prognostic study using cohort data suggest that tree-based ensemble machine learning models could accurately predict adults at risk of foregoing preventive dental care and demonstrated bias against underrepresented sociodemographic groups. These results highlight the importance of evaluating model fairness during development and testing to avoid exacerbating existing biases.