Matej Jelenc, Miljana Shulajkovska, Rok Jurič and Anton Gradišek

Abstract
Root canal treatment is a medical procedure aimed at preventing or
treating apical periodontitis, which is an inflammation around the
apex of a tooth root. In this study, we analyzed a dataset collected
by an experienced practitioner over the course of several years,
and developed a forecasting model, based on the XGBoost algorithm,
to predict the outcome of the treatment. The trained models
achieved a mean area under the receiver-operating-characteristic
curve (AUROC) of 0.92 and average precision (AP) of 0.77. We discuss
the importance of individual features in view of expert dental
knowledge. To assist the practitioner in daily practice, we developed
a web-based application to provide an assessment of treatment
outcomes.