Title: Data mining-based integration method of infant emergency and critical information in modern hospital

Authors: Juan Xiao; Jina Zhang; Xiaoli Liu

Addresses: College of Nursing, HeNan Medical College, ZhengZhou, 450000, China ' College of Nursing, HeNan Medical College, ZhengZhou, 450000, China ' Department of Nursing, The Second People's Hospital of Henan Province, ZhengZhou, 450000, China

Abstract: In this paper, a modern hospital infant emergency and critical information integration method based on data mining is designed. First of all, the data types of children's critical information in modern hospitals are analysed. Then, metadata is extracted through mapping relationship. Finally, the data missing value is filled in by the mean filling method, and the support and correlation of the data are calculated by the association rule algorithm, and the information integration model is constructed to realise the information data integration. The test results show that the error of the proposed method for the integration of children's emergency and critical information in modern hospitals is always lower than 0.3%, the throughput is always above 75 Mbps, and the maximum integration time is only 2.12 s, which has good practical application performance.

Keywords: data mining; modern hospitals; children are in critical condition; information integration; metadata; variable linear method.

DOI: 10.1504/IJDMB.2023.134294

International Journal of Data Mining and Bioinformatics, 2023 Vol.27 No.4, pp.312 - 325

Received: 24 Feb 2023
Accepted: 19 Jun 2023
Published online: 17 Oct 2023 *