Predicting early orthodontic treatment results and development of the dentofacial system without orthodontic treatment in 3-12-year-old children

Abstract

Relevance. Prognosis of the dentofacial system (DS) development in children with dentofacial deformities (DD) is an urgent medical and social problem since the prognosis of the DS development will allow timely prescription and provision of adequate therapy, which will significantly reduce the risks of severe DD development in children. Machine learning methods have proven to be a reliable tool for predicting a patient's health status and evaluating the effectiveness of treatment methods. Therefore, it seems interesting to use this modern toolkit to build predictive models that allow us to assess the change in the condition of DS in children with DD after orthodontic treatment (OT) at different ages or without OT. Purpose. The study aimed to build a set of predictive models for assessing the severity of the dentofacial system condition in 3.5-4-year-old children after and without orthodontic treatment. Material and methods. The study used the data on the DS of children aged 3-5 years (n=50), 6-9 years (n=100), 10-12 years (n=100) and 13-17 years (n =100). The author's program was developed in Python 3.11 using the sklearn, pandas, and xgb libraries in Anaconda to build the predictive models. Results. We developed nine models of the DS condition in children aged 3-12 years, three of which make predictions for the DS development after the OT (one - in the group of 3 – 5-year-old children, the second – in the group of 6 – 9-year-old children and the third – in the group of 10 – 12-year-olds) and six models predict the development of the DS without OT. Three out of 6 models predict DS development without OT at 3-5 years: the first makes a prediction of the DS condition for 6-9 year-olds; the second – for 10-12 year-olds; the third – for 13-17-year-olds. The accuracy of the models ranges from 82 to 86%. Two models out of 6 predict the DS development for children with DD who did not receive OT at 6-9 years old: one – at 10-12 years old, the second – at 13-17 years old. The accuracy of the models ranges from 92 to 97%. The sixth model makes predictions of the DS condition in children aged 13-17 years who did not receive OT at the age of 10-12 years. The accuracy of the model is 94%. In addition, we built three models that predict the DS condition in 3.5-4 years after the OT: the first model predicts for 3–5-year-old children; the second – for 6–9-year-olds; and the third - for children of 10–12 years old. The accuracy of the models ranges from 82 to 90%. Conclusion. All obtained models will be used to build a web application for predicting the DS state severity in children after the orthodontic treatment and without the latter.