Prediction of Return-to-original-work after an Industrial Accident Using Machine Learning and Comparison of Techniques.

ABSTRACT:

Background

Many studies have tried to develop predictors for return-to-work (RTW). However, since complex factors have been demonstrated to predict RTW, it is difficult to use them practically. This study investigated whether factors used in previous studies could predict whether an individual had returned to his/her original work by four years after termination of the worker's recovery period.

Methods

An initial logistic regression analysis of 1,567 participants of the fourth Panel Study of Worker's Compensation Insurance yielded odds ratios. The participants were divided into two subsets, a training dataset and a test dataset. Using the training dataset, logistic regression, decision tree, random forest, and support vector machine models were established, and important var

SUBMITTER: Lee J 

PROVIDER: S-EPMC5934520 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature