Ontology highlight
ABSTRACT: Objective
Workers' diseases and injuries are often highly related to work. However, due to limited resources and unclear work relatedness, workers' compensation insurance cannot cover all diseases or injuries among workers. This study aimed to estimate the status and probability of disapproval from national workers' compensation insurance using basic information from Korean workers' compensation system.Methods
The compensation insurance data for Korean workers consists of personal, occupational, and claims data. We describe the status of disapproval by workers' compensation insurance according to the type of disease or injury. A prediction model for disapproval by workers' compensation insurance was established by applying two machine-learning methods with a logistic regres
SUBMITTER: Choi SB
PROVIDER: S-EPMC9939877 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature