The Medical Diagnosis Support System with Intelligent Multiagent Techniques by Performance Differential Difference

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
ISSN
1883-3977
NCID
BB00577064