Predictors of tooth loss: A machine learning approach.

ABSTRACT:

Introduction

Little is understood about the socioeconomic predictors of tooth loss, a condition that can negatively impact individual's quality of life. The goal of this study is to develop a machine-learning algorithm to predict complete and incremental tooth loss among adults and to compare the predictive performance of these models.

Methods

We used data from the National Health and Nutrition Examination Survey from 2011 to 2014. We developed multiple machine-learning algorithms and assessed their predictive performances by examining the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and positive and negative predictive values.

Results

The extreme gradient boosting trees presented the highest performance in the pred

SUBMITTER: Elani HW 

PROVIDER: S-EPMC8213149 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature