帕金森病患者运动状态的自动评估——案例研究。
Automatic assessment of the motor state of the Parkinson's disease patient--a case study.
机构信息
Multimedia Systems Department, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdansk, Poland.
出版信息
Diagn Pathol. 2012 Feb 19;7:18. doi: 10.1186/1746-1596-7-18.
UNLABELLED
This paper presents a novel methodology in which the Unified Parkinson's Disease Rating Scale (UPDRS) data processed with a rule-based decision algorithm is used to predict the state of the Parkinson's Disease patients. The research was carried out to investigate whether the advancement of the Parkinson's Disease can be automatically assessed. For this purpose, past and current UPDRS data from 47 subjects were examined. The results show that, among other classifiers, the rough set-based decision algorithm turned out to be most suitable for such automatic assessment.
VIRTUAL SLIDES
The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1563339375633634.
未标注
本文提出了一种新方法，该方法使用基于规则的决策算法处理统一帕金森病评定量表（UPDRS）数据，以预测帕金森病患者的状态。该研究旨在探讨是否可以自动评估帕金森病的进展。为此，检查了 47 名受试者的过去和当前 UPDRS 数据。结果表明，在其他分类器中，基于粗糙集的决策算法最适合这种自动评估。
虚拟幻灯片
本文的虚拟幻灯片可在此处找到：http://www.diagnosticpathology.diagnomx.eu/vs/1563339375633634。
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