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Application of Data Mining Technology in Analysis of Hierarchical Nursing Effects

Binbin Ji, Yujia Ren, Siyuan Tang


Data mining refers to a process of extracting hidden, previously unknown but potentially useful information and knowledge from massive, incomplete, noisy, vague and random actual application data, to enable people to discover useful new rules and new concepts, and improve researchers’ deep understanding, knowledge and application of a large amount of original data. As a scientific and standardized management method, hierarchical nursing can help improve the overall quality of nurses, enhance the quality of nursing services, and improve patients’ satisfaction. Data mining technology combined with neural network and decision tree models could be used to study the influence of hierarchical nursing on family accompany rate and patients’ satisfaction, and discuss about the effects of applying data mining technology to the analysis of hierarchical nursing effects, and it is also an effective method to help hospitals improve service quality and strengthen clinical management.


data mining, neural network, decision tree, hierarchical nursing, patients’ satisfaction.

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