| An associative memory approach to medical decision support systems. | |
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MedLine Citation:
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PMID: 21703713 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Classification is one of the key issues in medical diagnosis. In this paper, a novel approach to perform pattern classification tasks is presented. This model is called Associative Memory based Classifier (AMBC). Throughout the experimental phase, the proposed algorithm is applied to help diagnose diseases; particularly, it is applied in the diagnosis of seven different problems in the medical field. The performance of the proposed model is validated by comparing classification accuracy of AMBC against the performance achieved by other twenty well known algorithms. Experimental results have shown that AMBC achieved the best performance in three of the seven pattern classification problems in the medical field. Similarly, it should be noted that our proposal achieved the best classification accuracy averaged over all datasets. |
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Authors:
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Mario Aldape-Pérez; Cornelio Yáñez-Márquez; Oscar Camacho-Nieto; Amadeo J Argüelles-Cruz |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-6-22 |
Journal Detail:
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Title: Computer methods and programs in biomedicine Volume: - ISSN: 1872-7565 ISO Abbreviation: - Publication Date: 2011 Jun |
Date Detail:
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Created Date: 2011-6-27 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8506513 Medline TA: Comput Methods Programs Biomed Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Copyright Information:
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Copyright © 2011 Elsevier Ireland Ltd. All rights reserved. |
Affiliation:
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Center for Computing Research, CIC-IPN Building, Nueva Industrial Vallejo, G.A. Madero, Mexico City 07738, Mexico; Superior School of Computing, ESCOM-IPN Building, Lindavista, G.A. Madero, Mexico City 07738, Mexico. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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