Diagnosing Parkinson's Diseases Using Fuzzy Neural System

被引：24

作者：

Abiyev, Rahib H. ^{[1
]}

Abizade, Sanan ^{[2
]}

机构：

[1] Near East Univ, Dept Comp Engn, Appl Artificial Intelligence Res Ctr, TR-10 Mersin, Turkey

[2] Near East Univ, Dept Elect & Elect Engn, Appl Artificial Intelligence Res Ctr, TR-10 Mersin, Turkey

来源：

COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE | 2016年 / 2016卷

关键词：

TIME-SERIES PREDICTION; CLASSIFICATION; NETWORKS; MODELS;

D O I：

10.1155/2016/1267919

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

This study presents the design of the recognition system that will discriminate between healthy people and people with Parkinson's disease. A diagnosing of Parkinson's diseases is performed using fusion of the fuzzy system and neural networks. The structure and learning algorithms of the proposed fuzzy neural system (FNS) are presented. The approach described in this paper allows enhancing the capability of the designed system and efficiently distinguishing healthy individuals. It was proved through simulation of the system that has been performed using data obtained from UCI machine learning repository. A comparative study was carried out and the simulation results demonstrated that the proposed fuzzy neural system improves the recognition rate of the designed system.

引用

页数：9

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