Fuzzy rule-based system applied to risk estimation of cardiovascular patients

Bohacik, Jan; Davis, Darryl N.

Abstract

Cardiovascular decision support is one area of increasing research interest. On-going collaborations between clinicians and computer scientists are looking at the application of knowledge discovery in databases to the area of patient diagnosis, based on clinical records. A fuzzy rule-based system for risk estimation of cardiovascular patients is proposed. It uses a group of fuzzy rules as a knowledge representation about data pertaining to cardiovascular patients. Several algorithms for the discovery of an easily readable and understandable group of fuzzy rules are formalized and analysed. The accuracy of risk estimation and the interpretability of fuzzy rules are discussed. Our study shows, in comparison to other algorithms used in knowledge discovery, that classifcation with a group of fuzzy rules is a useful technique for risk estimation of cardiovascular patients. © 2013 Old City Publishing, Inc.

Citation

Bohacik, J., & Davis, D. N. (2013). Fuzzy rule-based system applied to risk estimation of cardiovascular patients. Journal of Multiple-Valued Logic and Soft Computing, 20(5-6), 445-466

• Journal Article Type: Article
• Publication Date: May 13, 2013
• Deposit Date: Nov 13, 2014
• Publicly Available Date: Nov 13, 2014
• Journal: Journal of Multiple-Valued Logic and Soft Computing
• Print ISSN: 1542-3980
• Publisher: Old City Publishing
• Peer Reviewed: Peer Reviewed
• Volume: 20
• Issue: 5-6
• Pages: 445-466
• Keywords: Classification, Fuzzy rules, Linguistic variable elimination, Cumulative information estimations, Classification ambiguity, Medical data mining, Cardiology
• Public URL: https://hull-repository.worktribe.com/output/465994
• Publisher URL: http://www.oldcitypublishing.com/journals/mvlsc-home/mvlsc-issue-contents/mvlsc-volume-20-number-5-6-2013/mvlsc-20-5-6-p-445-466/
• Additional Information: Authors' accepted manuscript of article published in: Journal of multiple-valued logic and soft computing, 2013, v.20, issue 5-6
• Contract Date: Nov 13, 2014