Methods for the Intelligent Analysis of Biomedical Data

Эмилия Гегерь, E. Geger, Александр Подвесовский, A. Podvesovskiy, Сергей Кузьмин, S. Kuzmin, Виктория Толстенок, Viktoriya Tolstenok
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Abstract

The paper discusses methodology of cleaning and analysis of small semi-structured samples of biomedical data. This methodology is aimed at statistical evaluation of harmful production factor correlation with workers’ laboratory test data. As a result of the analysis and interpretation of the data, a deviation from the norm is observed according to some indicators of a clinical blood test in individuals whose occupational activity is associated with harmful factors. Conclusions are drawn about the need for further research in the group of people whose work is related to harmful production factors. It is necessary to employ intelligent methods for analyzing possible health risks and their negative consequences in order to make management decisions. The presented assessment methodology can be used to create an occupational health and safety information system.
生物医学数据的智能分析方法
本文讨论了生物医学数据小型半结构化样本的清洗和分析方法。该方法旨在统计评估有害生产因素与工人实验室测试数据的相关性。对数据进行分析和解释的结果是,根据职业活动与有害因素有关的个人的临床血液检查的一些指标,观察到与规范的偏差。结论是需要对工作与有害生产因素有关的人群进行进一步研究。有必要采用智能方法来分析可能的健康风险及其负面后果,以便做出管理决策。所提出的评估方法可用于建立职业健康与安全信息系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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