AMI screening using linguistic fuzzy rules

This paper aims at identifying the factors that would help to diagnose acute myocardial infarction (AMI) using data from an electronic medical record system (EMR) and then generating structure decisions in the form of linguistic fuzzy rules to help predict and understand the outcome of the diagnosis...

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Main Authors: Ainon, R.N., Bulgiba, Awang, Lahsasna, A.
Format: Article
Language:English
Published: Springer Verlag 2010
Subjects:
Online Access:http://eprints.um.edu.my/3072/1/AMI_Screening_Using_Linguistic_Fuzzy_Rules.pdf
http://eprints.um.edu.my/3072/
http://www.springerlink.com/content/2h32x2m6gk204557/
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spelling my.um.eprints.30722019-08-26T06:40:51Z http://eprints.um.edu.my/3072/ AMI screening using linguistic fuzzy rules Ainon, R.N. Bulgiba, Awang Lahsasna, A. R Medicine This paper aims at identifying the factors that would help to diagnose acute myocardial infarction (AMI) using data from an electronic medical record system (EMR) and then generating structure decisions in the form of linguistic fuzzy rules to help predict and understand the outcome of the diagnosis. Since there is a tradeoff in the fuzzy system between the accuracy which measures the capability of the system to predict the diagnosis of AMI and transparency which reflects its ability to describe the symptoms-diagnosis relation in an understandable way, the proposed fuzzy rules are designed in a such a way to find an appropriate balance between these two conflicting modeling objectives using multi-objective genetic algorithms. The main advantage of the generated linguistic fuzzy rules is their ability to describe the relation between the symptoms and the outcome of the diagnosis in an understandable way, close to human thinking and this feature may help doctors to understand the decision process of the fuzzy rules. Springer Verlag 2010 Article PeerReviewed application/pdf en http://eprints.um.edu.my/3072/1/AMI_Screening_Using_Linguistic_Fuzzy_Rules.pdf Ainon, R.N. and Bulgiba, Awang and Lahsasna, A. (2010) AMI screening using linguistic fuzzy rules. Journal of Medical Systems, 36 (2). pp. 463-473. ISSN 0148-5598 http://www.springerlink.com/content/2h32x2m6gk204557/ 10.1007/s10916-010-9491-2
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
language English
topic R Medicine
spellingShingle R Medicine
Ainon, R.N.
Bulgiba, Awang
Lahsasna, A.
AMI screening using linguistic fuzzy rules
description This paper aims at identifying the factors that would help to diagnose acute myocardial infarction (AMI) using data from an electronic medical record system (EMR) and then generating structure decisions in the form of linguistic fuzzy rules to help predict and understand the outcome of the diagnosis. Since there is a tradeoff in the fuzzy system between the accuracy which measures the capability of the system to predict the diagnosis of AMI and transparency which reflects its ability to describe the symptoms-diagnosis relation in an understandable way, the proposed fuzzy rules are designed in a such a way to find an appropriate balance between these two conflicting modeling objectives using multi-objective genetic algorithms. The main advantage of the generated linguistic fuzzy rules is their ability to describe the relation between the symptoms and the outcome of the diagnosis in an understandable way, close to human thinking and this feature may help doctors to understand the decision process of the fuzzy rules.
format Article
author Ainon, R.N.
Bulgiba, Awang
Lahsasna, A.
author_facet Ainon, R.N.
Bulgiba, Awang
Lahsasna, A.
author_sort Ainon, R.N.
title AMI screening using linguistic fuzzy rules
title_short AMI screening using linguistic fuzzy rules
title_full AMI screening using linguistic fuzzy rules
title_fullStr AMI screening using linguistic fuzzy rules
title_full_unstemmed AMI screening using linguistic fuzzy rules
title_sort ami screening using linguistic fuzzy rules
publisher Springer Verlag
publishDate 2010
url http://eprints.um.edu.my/3072/1/AMI_Screening_Using_Linguistic_Fuzzy_Rules.pdf
http://eprints.um.edu.my/3072/
http://www.springerlink.com/content/2h32x2m6gk204557/
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