Identifying predictors of tooth loss using a rule‐based machine learning approach: A retrospective study at university‐setting clinics

Abstract

The two-step machine learning pipeline is feasible to predict tooth loss in periodontitis patients. Compared to classical statistical methods, this rule-based machine learning approach improves model explainability. However, the model's generalizability needs to be further validated by external datasets.