Design of a fuzzy-based decision support system for coronary heart disease diagnosis
In the present paper, a fuzzy rule-based system (FRBS) is designed to serve as a decision support system for Coronary heart disease (CHD) diagnosis that not only considers the decision accuracy of the rules but also their transparency at the same time. To achieve the two above mentioned objectives,...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Springer Verlag
2012
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/3050/1/Design_of_a_Fuzzy-based_Decision_Support_System_for_Coronary_Heart_Disease_Diagnosis.pdf |
| _version_ | 1825718750398119936 |
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| author | Lahsasna, A. Ainon, R.N. Zainuddin, R. Bulgiba, Awang |
| author_facet | Lahsasna, A. Ainon, R.N. Zainuddin, R. Bulgiba, Awang |
| author_sort | Lahsasna, A. |
| collection | UM |
| description | In the present paper, a fuzzy rule-based system (FRBS) is designed to serve as a decision support system for Coronary heart disease (CHD) diagnosis that not only considers the decision accuracy of the rules but also their transparency at the same time. To achieve the two above mentioned objectives, we apply a multi-objective genetic algorithm to optimize both the accuracy and transparency of the FRBS. In addition and to help assess the certainty and the importance of each rule by the physician, an extended format of fuzzy rules that incorporates the degree of decision certainty and importance or support of each rule at the consequent part of the rules is introduced. Furthermore, a new way for employing Ensemble Classifiers Strategy (ECS) method is proposed to enhance the classification ability of the FRBS. The results show that the generated rules are humanly understandable while their accuracy compared favorably with other benchmark classification methods. In addition, the produced FRBS is able to identify the uncertainty cases so that the physician can give a special consideration to deal with them and this will result in a better management of efforts and tasks. Furthermore, employing ECS has specifically improved the ability of FRBS to detect patients with CHD which is desirable feature for any CHD diagnosis system. |
| first_indexed | 2024-03-06T05:09:08Z |
| format | Article |
| id | um.eprints-3050 |
| institution | Universiti Malaya |
| language | English |
| last_indexed | 2024-03-06T05:09:08Z |
| publishDate | 2012 |
| publisher | Springer Verlag |
| record_format | dspace |
| spelling | um.eprints-30502019-08-26T06:38:10Z http://eprints.um.edu.my/3050/ Design of a fuzzy-based decision support system for coronary heart disease diagnosis Lahsasna, A. Ainon, R.N. Zainuddin, R. Bulgiba, Awang R Medicine In the present paper, a fuzzy rule-based system (FRBS) is designed to serve as a decision support system for Coronary heart disease (CHD) diagnosis that not only considers the decision accuracy of the rules but also their transparency at the same time. To achieve the two above mentioned objectives, we apply a multi-objective genetic algorithm to optimize both the accuracy and transparency of the FRBS. In addition and to help assess the certainty and the importance of each rule by the physician, an extended format of fuzzy rules that incorporates the degree of decision certainty and importance or support of each rule at the consequent part of the rules is introduced. Furthermore, a new way for employing Ensemble Classifiers Strategy (ECS) method is proposed to enhance the classification ability of the FRBS. The results show that the generated rules are humanly understandable while their accuracy compared favorably with other benchmark classification methods. In addition, the produced FRBS is able to identify the uncertainty cases so that the physician can give a special consideration to deal with them and this will result in a better management of efforts and tasks. Furthermore, employing ECS has specifically improved the ability of FRBS to detect patients with CHD which is desirable feature for any CHD diagnosis system. Springer Verlag 2012 Article PeerReviewed application/pdf en http://eprints.um.edu.my/3050/1/Design_of_a_Fuzzy-based_Decision_Support_System_for_Coronary_Heart_Disease_Diagnosis.pdf Lahsasna, A. and Ainon, R.N. and Zainuddin, R. and Bulgiba, Awang (2012) Design of a fuzzy-based decision support system for coronary heart disease diagnosis. Journal of Medical Systems. pp. 1-14. ISSN 0148-5598, DOI https://doi.org/10.1007/s10916-012-9821-7 <https://doi.org/10.1007/s10916-012-9821-7>. http://www.springerlink.com/content/m7w6r143l278n7j4/ doi:10.1007/s10916-012-9821-7 |
| spellingShingle | R Medicine Lahsasna, A. Ainon, R.N. Zainuddin, R. Bulgiba, Awang Design of a fuzzy-based decision support system for coronary heart disease diagnosis |
| title | Design of a fuzzy-based decision support system for coronary heart disease diagnosis |
| title_full | Design of a fuzzy-based decision support system for coronary heart disease diagnosis |
| title_fullStr | Design of a fuzzy-based decision support system for coronary heart disease diagnosis |
| title_full_unstemmed | Design of a fuzzy-based decision support system for coronary heart disease diagnosis |
| title_short | Design of a fuzzy-based decision support system for coronary heart disease diagnosis |
| title_sort | design of a fuzzy based decision support system for coronary heart disease diagnosis |
| topic | R Medicine |
| url | http://eprints.um.edu.my/3050/1/Design_of_a_Fuzzy-based_Decision_Support_System_for_Coronary_Heart_Disease_Diagnosis.pdf |
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