| Comparing regularized B-spline neural network, multilayer perceptron and boosted-CART on two problems of heart arrhythmia diagnosis. | |
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MedLine Citation:
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PMID: 17271070 Owner: NLM Status: PubMed-not-MEDLINE |
Abstract/OtherAbstract:
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Medical diagnosis has special requirements on reliability and interpretability of a learning scheme. Two problems in heart arrhythmia diagnosis are discussed in the paper 1) distinguish premature ventricular contraction beats from normal beats (Problem A); 2) distinguish premature ventricular contraction beats from premature atrial beats (Problem B). Analysis of the real clinical data shows that these two problems have different noise levels, which is suitable for addressing various requirements of medical domain. The performances and characteristics of three methods are compared: Regularized B-spline Neural Networks, Multilayer Perceptron and Boosted-CART using AdaBoost. Regularized B-spline Neural Network outperforms Multilayer Perceptron on the difficult Problem B, which suggests its potential in modeling complex system. Overall, Boosted-CART achieves best recognition rate with intermediate interpretability. |
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Authors:
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Jie Zhou |
Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference Volume: 5 ISSN: 1557-170X ISO Abbreviation: Conf Proc IEEE Eng Med Biol Soc Publication Date: 2004 |
Date Detail:
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Created Date: 2007-02-02 Completed Date: 2007-06-08 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101243413 Medline TA: Conf Proc IEEE Eng Med Biol Soc Country: United States |
Other Details:
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Languages: eng Pagination: 3601-4 Citation Subset: - |
Affiliation:
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Department of Computer Science, Northern Illinois University, DeKalb, IL 60115, USA. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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