DocumentCode :
3699119
Title :
Research on prediction method for pivotal indicator of hospital medical quality using decision tree
Author :
Liujian Chen;Lujia Bi;Huayou Si;Jilin Zhang;Yongjian Ren
Author_Institution :
Key Laboratory of Complex System Modeling and Simulation, Ministry of Education, Department of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, Zhejiang Province, China
fYear :
2015
Firstpage :
247
Lastpage :
250
Abstract :
Indicators of medical quality is the main basis of medical quality evaluation, predictive analyzing the indicators by using data mining technology, we can find and solve the problems of hospital quality management more timely. The study, basing on the medical homepage records, analyzes the key indicators of the hospital medical quality by decision tree C4.5 algorithm. Decision tree is a prediction model which can assist hospital to make related decision on medical quality management issues. By using decision tree C4.5 algorithm with appropriate modification, a high quality model of decision tree can be made. It can not only do the statistic of medical quality indicators, but also predict the indicators with high relative accuracy to improve hospital´s medical quality management.
Keywords :
"Hospitals","Decision trees","Classification algorithms","Data mining","Training","Predictive models"
Publisher :
ieee
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2015 6th IEEE International Conference on
ISSN :
2327-0586
Print_ISBN :
978-1-4799-8352-0
Electronic_ISBN :
2327-0594
Type :
conf
DOI :
10.1109/ICSESS.2015.7339047
Filename :
7339047
Link To Document :
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