Paper Info
Title
Abnormal Event Health-Status Monitoring Based on Multi-Dimensional and Multi-Level Association Rules Constraints in Nursing Information System
Abstract
Since the traditional methods such as statistical analysis are used to analyze the long-term nursing service strategy more, and no association rule method is used to solve the problems encountered in the development of long-term nursing service. This paper aims to provide some data support for the establishment of a scientific and reasonable long-term nursing information system by synthesizing the basic national conditions and drawing lessons from foreign experience. Therefore, in order to improve the analytical accuracy of multidimensional multi-model data, minimal rule which includes rules with single item as the consequent and the minimal number of items as the antecedent, can be introduced to derive the same decisions as other association rules without information loss, while the number of minimal rules is much less than of all rules. From these association rules, it can be known that diabetes has a strong association with coronary heart disease, hypertension, fatty liver, chronic arterial occlusive disease, abnormal lipid metabolism and other diseases; according to the analysis of the antecedent and consequence in the results table of the above association rules, it can be found that diabetes is highly likely to cause hypertension, coronary heart disease, abnormal lipid metabolism, fatty liver, and there is a close relationship between various complications.
Year
DOI
Venue
2020
10.1166/jmihi.2020.2964
JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS
Keywords
DocType
Volume
Abnormal Event,Health-Status Monitoring,Association Rule,Data Mining,Nursing Information System,Multi-Dimensional,Multi-Level
Journal
10
Issue
ISSN
Citations 
3
2156-7018
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Mingjing Fang100.34
Yingying Xu200.34
Qionghua Yin300.34
Jianhong Yu400.34
Can Wang500.34
Yingying Zhang615016.21