Evaluation of different machine learning algorithms for extraction decision in orthodontic treatment.

ABSTRACT:

Introduction

The extraction decision significantly affects the treatment process and outcome. Therefore, it is crucial to make this decision with a more objective and standardized method. The objectives of this study were (1) to identify the best-performing model among seven machine learning (ML) models, which will standardize the extraction decision and serve as a guide for inexperienced clinicians, and (2) to determine the important variables for the extraction decision.

Methods

This study included 1000 patients who received orthodontic treatment with or without extraction (500 extraction and 500 non-extraction). The success criteria of the study were the decisions made by the four experienced orthodontists. Seven ML models were trained using 36 variables; including demogr

SUBMITTER: Kokturk B 

PROVIDER: S-EPMC11654355 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature