Predicting workplace absenteeism using machine learning: a pilot study in occupational health

Abstract

This pilot study demonstrates the feasibility of machine learning approaches for occupational health management by enabling identification of employees at risk for prolonged absenteeism. While showing promise for supporting personalized health interventions and resource allocation, implementation requires external validation across multiple organizations and careful consideration of ethical implications regarding employee privacy and algorithmic fairness.

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