Analysis using Adaptive Tree Structured Clustering Method for Medical Data of Patients with Coronary Heart Disease
Fourth International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2008
Page 139-144
published_at 2008-12
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Title ( eng ) |
Analysis using Adaptive Tree Structured Clustering Method for Medical Data of Patients with Coronary Heart Disease
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Creator |
Yamaguchi Takashi
Ichimura Takumi
Mackin Kenneth J.
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Source Title |
Fourth International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2008
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Start Page | 139 |
End Page | 144 |
Abstract |
It is known that the classification of medical data is difficult problem because the medical data has ambiguous information or missing data. As a result, the classification method that can handle ambiguous information or missing data is necessity. In this paper we proposed an adaptive tree structure clustering method in order to clarify clustering result of selforganizing feature maps. For the evaluating effectiveness of proposed clustering method for the data set with ambiguous information, we applied an adaptive tree structured clustering method for classification of coronary heart disease database. Through the computer simulation we showed that the proposed clustering method was effective for the ambiguous data set.
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NDC |
Technology. Engineering [ 500 ]
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Language |
eng
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Resource Type | conference paper |
Publisher |
IEEE SMC Hiroshima Chapter
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Date of Issued | 2008-12 |
Rights |
(c) Copyright by IEEE SMC Hiroshima Chapter.
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Publish Type | Version of Record |
Access Rights | open access |
Source Identifier |
[ISSN] 1883-3977
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