ГРНТИ 50.07 Теоретические основы вычислительной техники
ББК 3297 Вычислительная техника
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.
risk assessment, data analysis, harmful working conditions, statistical methods, data cleaning, model ensembles, Kohonen self-organizing maps
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