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Measuring the effectiveness of hospital-acquired infection prevention

机译:测量医院获得的感染预防的有效性

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This article deals with data on nosocomial infections acquired in the Geneva University Hospitals. Goal of the work is to derive a model from a hospital-acquired infection (HAI) prevalence survey of year Y and apply them to a prevalence survey of years 7+7, Y+2. This analysis permits to evaluate the effectiveness of preventive measures taken after the prevalence survey in year Y. It also analyzes the robustness of the SVM algorithm on time-variable attributes. The model build on the dataset of year Ygives better results than in a previous study. The application of the model on the Y+l and Y+2 prevalence surveys shows simultaneously improvements and deteriorations of 5 performance measures. This highlights the effectiveness of prevention and reduces the risk of HAI after the prevalence survey of year Y. We introduce a new method to detect redundancy in a dataset with the SVM algorithm.
机译:本文涉及日内瓦大学医院获得的医院感染数据。该工作的目标是从一年的医院收购的感染(HAI)患病率调查中获得模型,并将其应用于多年7 + 7,Y + 2的患病率调查。该分析允许评估在Y的患病率调查中采取的预防措施的有效性。它还分析了SVM算法在时间变量属性上的稳健性。模型在年份的数据集上建立了比以前的研究更好的结果。模型在Y + L和Y + 2流行调查中的应用同时提高了5种性能措施的改进和劣化。这突出了预防的有效性,并减少了对年度的患病率调查后海的风险。我们介绍了一种用SVM算法检测数据集中的冗余方法。

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