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Comparative Study
. 2016:2016:1267919.
doi: 10.1155/2016/1267919. Epub 2016 Jan 10.

Diagnosing Parkinson's Diseases Using Fuzzy Neural System

Rahib H Abiyev  1 , Sanan Abizade  2
Affiliations
Comparative Study

Diagnosing Parkinson's Diseases Using Fuzzy Neural System

Rahib H Abiyev et al. Comput Math Methods Med. 2016.

Abstract

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.

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Figures

Figure 1
Figure 1
Classifier based on FNS.
Figure 2
Figure 2
RMSE values.
See this image and copyright information in PMC

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