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ID 19676
Eprint ID
19676
FullText URL
Author
Nakano Kazuyoshi
Yamaguchi Daisuke
Katayama Fumiyo
Takahashi Muneo
Abstract
Multiagent technologies enable us to explore their sociological and psychological foundations. A medical diagnostic support system is built using this. Moreover, We think that the data inputted can acquire higher diagnostic accuracy by sorting out using a determination table. In this paper, the recurrence diagnostic system of cancer is built and the output error of Multiagent learning method into the usual Neural Network and a Rough Neural Network and Genetic Programming be compared. The data of the prostatic cancer offered by the medical institution and a renal cancer was used for verification of a system. Inspection data of the renal cancer consist of special data. We think improvement of the precision of a system which using the data from initial value of the network.
Keywords
Intelligent Multiagent System
Neural Networks
Medical Diagnostic Support System
Published Date
2009-11-10
Publication Title
Proceedings : Fifth International Workshop on Computational Intelligence & Applications
Volume
volume2009
Issue
issue1
Publisher
IEEE SMC Hiroshima Chapter
Start Page
192
End Page
195
ISSN
1883-3977
NCID
BB00577064
Content Type
Conference Paper
language
English
Copyright Holders
IEEE SMC Hiroshima Chapter
Event Title
5th International Workshop on Computational Intelligence & Applications IEEE SMC Hiroshima Chapter : IWCIA 2009
Event Location
東広島市
Event Location Alternative
Higashi-Hiroshima City
File Version
publisher
Refereed
True
Eprints Journal Name
IWCIA