Diagnosis of Parkinson s disease via Support Vector Machine optimized by Optimal Particle Swarm Algorithm
Publish Year: 1398
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
NREAS02_147
تاریخ نمایه سازی: 12 مرداد 1399
Abstract:
Parkinson s disease (PD) is one of the most common diseases in the world and it is crucial to identify in the early stages of the disease. If the reliable diagnosis is available, the patient can be treated at the right time. Therefore, artificial intelligent algorithms play an important role in the early proper treatment of the disease. In this study, Parkinson s disease is detected by support vector machine and dimension of data is reduced using particle swarm optimization algorithm. The data are the voice recordings of patients consist of ۲۲ features. The proposed method diagnoses PD with ۹۷% accuracy when the number of features is reduced to ۷ attributes. Comparing the method with other state-of-the-art studies shows the superiority of proposed method
Keywords:
Feature Selection , Particle Swarm Optimization Algorithm (PSO) , Support Vector Machine (SVM) , Parkinson s disease (PD).
Authors
Zeinab Hassani
Faculty of Computer Science, Kosar University of Bojnord, Bojnord, Iran
Najmeh Samadyani
Faculty of Computer Science, Kosar University, Bojnord, Iran