PD-ADSV: An automated diagnosing system using voice signals and hard voting ensemble method for Parkinson's disease

被引：5
作者：
Ghaheri, Paria [1 ]
Shateri, Ahmadreza [1 ]
Nasiri, Hamid [2 ]
机构：
[1] Semnan Univ, Elect & Comp Engn Dept, Semnan, Iran
[2] Amirkabir Univ Technol, Dept Comp Engn, Tehran Polytech, Tehran, Iran
来源：
SOFTWARE IMPACTS | 2023年 / 16卷
关键词：
Gradient Boosting; LightGBM; Parkinson's disease; XGBoost; SELECTION; FEATURES;
D O I：
10.1016/j.simpa.2023.100504
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
Parkinson's disease (PD) is the most widespread movement condition and the second most common neurode-generative disorder, following Alzheimer's. Movement symptoms and imaging techniques are the most popular ways to diagnose this disease. However, they are not accurate and fast and may only be accessible to a few people. This study provides an autonomous system, i.e., PD-ADSV, for diagnosing PD based on voice signals, which uses four machine learning classifiers and the hard voting ensemble method to achieve the highest accuracy. PD-ADSV is developed using Python and the Gradio web framework.
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收藏
页数：5
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