This study investigates the impact of workplace accidents or illnesses leading to lowerbackconditions on an individual’s ability to return to work. Using medical data analysis, it aims to identify predictive factor...
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This study investigates the impact of workplace accidents or illnesses leading to lowerbackconditions on an individual’s ability to return to work. Using medical data analysis, it aims to identify predictive factors, including rest justification and invalidity. The research utilizes a decisiontreealgorithm to predict return-to-work ability. Significant predictors include age, height, general health status, civil status, scarring, number of children, body mass index, weight, toe walking, limping, respiratory issues, marriage, and professional sector. The decisiontree model demonstrates high efficiency and accuracy, providing valuable insights for evidence-based strategies to improve return-to-work outcomes in lowerback condition cases.
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