A hybrid approach to predicting and classifying dental impaction: integrating regularized regression and XG boost methods

The study aims to improve dental research by predicting the eruption behavior of lower molars, enabling dental practitioners to make more concise treatment plans. The study identifies the most significant parameters for establishing the space/width ratio: Distance from the second molar to the anterior ramus border and the third molar's mesiodistal width. Enhancing data quality, refining feature selection, and using advanced modeling techniques are crucial for improving predictive capabilities. The findings can help practitioners optimize treatments and reduce potential complications.