Analysis of Fuzzy Decision Trees on Expert Fuzzified Heart Failure Data

被引：0

作者：

Bohacik, Jan ^{[1
,3
,4
]}

Kambhampati, C. ^{[1
]}

Davis, Darryl N. ^{[1
]}

Cleland, J. F. G. ^{[2
]}

机构：

[1] Univ Hull, Dept Comp Sci, Kingston Upon Hull HU6 7RX, N Humberside, England

[2] Univ Hull, Dept Cardiol, Kingston Upon Hull HU6 7RX, N Humberside, England

[3] Univ Zilina, Dept Comp Sci, Zilina, Slovakia

[4] Univ Zilina, Dept Informat, Zilina, Slovakia

来源：

2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013) | 2013年

关键词：

fuzzy decision tree; fuzzy rules; fuzzification; cardiology; heart failure; MORTALITY; INDUCTION;

D O I：

10.1109/SMC.2013.66

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

The prevalence of heart failure is 2-3% of the adult population and it is expected to grow. Half of all patients diagnosed with it die within four years. To minimize life-threatening situations and to minimize costs, it is interesting to predict mortality rates for a patient with heart failure. In this paper, a fuzzy decision tree based on classification ambiguity and a fuzzy decision tree based on cumulative information estimations are presented. They are employed on a heart failure data fuzzified on the basis of medical expert knowledge. After a transformation of fuzzy decision trees, the use of medical expert knowledge allows us to create a group of fuzzy rules that is easily interpretable by medical experts. Our study shows that different types of fuzzy decision trees can have significantly different accuracy results and interpretability.

引用

页码：350 / 355

页数：6

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