TabNet-RUSBoost 하이브리드 모델을 이용한 산업재해 근로자의 직장 복귀 예측: ICF 모델의 적용 Predicting Return-to-Work Outcomes for Workers Injured in Industrial Accidents Using a TabNet-RUSBoost Hybrid Model: Incorporating the ICF Framework
한국기계기술학회지
(韓國機械技術學會誌)
제26권 제3호
(2024.06)
pp.550-557
pp.550-557
한국기계기술학회
(Korean Society of Mechanical Technology)
초록
This study aims to predict return-to-work outcomes for workers injured in industrial accidents using a TabNet-RUSBoost hybrid model. The study analyzed data from 1,383 workers who had completed recuperation. Key predictors identified include length of recuperation, disability grade, occupation activity, self-efficacy, and socioeconomic status. The model effectively addresses class imbalance and demonstrates superior predictive performance. These findings underscore the importance of a holistic approach, incorporating both medical and psychosocial factors.
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