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Identification and classification of high risk groups for Coal Workers Pneumoconiosis using an artificial neural network based on occupational histories: a retrospective cohort study

机译:基于职业历史的人工神经网络对煤矿工人尘肺高危人群的识别和分类:一项回顾性队列研究

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摘要

BackgroundCoal workers' pneumoconiosis (CWP) is a preventable, but not fully curable occupational lung disease. More and more coal miners are likely to be at risk of developing CWP owing to an increase in coal production and utilization, especially in developing countries. Coal miners with different occupational categories and durations of dust exposure may be at different levels of risk for CWP. It is necessary to identify and classify different levels of risk for CWP in coal miners with different work histories. In this way, we can recommend different intervals for medical examinations according to different levels of risk for CWP. Our findings may provide a basis for further emending the measures of CWP prevention and control.
机译:背景技术煤矿工人的尘肺病(CWP)是一种可预防但不能完全治愈的职业性肺病。由于煤炭生产和利用的增加,越来越多的煤矿工人有发展煤电的风险,特别是在发展中国家。具有不同职业类别和接触粉尘时间的煤矿工人面临的CWP风险水平可能不同。有必要确定和分类具有不同工作经历的煤矿工人的CWP风险等级不同。这样,我们可以根据CWP风险的不同程度建议不同的间隔时间进行体检。我们的发现可能为进一步修订CWP预防和控制措施提供依据。

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