Analysis using Adaptive Tree Structured Clustering Method for Medical Data of Patients

URI http://harp.lib.hiroshima-u.ac.jp/hiroshima-cu/metadata/2974
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Title
Analysis using Adaptive Tree Structured Clustering Method for Medical Data of Patients
Author
氏名 YAMAGUCHI Takashi
ヨミ ヤマグチ タカシ
別名 市村 匠
氏名 ICHIMURA Takumi
ヨミ イチムラ タクミ
別名
氏名 MACKIN Kenneth J.
ヨミ マッキン ケネスジェームス
別名
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 self-organizing 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.

Description Peer Reviewed
Journal Title
Fourth International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2008
Spage
139
Epage
144
Published Date
2008-12
Publisher
IEEE SMC Hiroshima Chapter
ISSN
1883-3977
Language
eng
NIIType
Conference Paper
Text Version
出版社版
Rights
©Copyright by IEEE SMC Hiroshima Chapter. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE
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hiroshima-cu