Analysis of Parkinson’s Disease Data
Analysis of Parkinson’s Disease Data
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帕金森病数据分析
DOI：
10.1016/j.procs.2018.10.306
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
C. Dagli
中科院分区：
文献类型：
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作者：
Ram Deepak Gottapu;C. Dagli
在本文中，我们调查的诊断数据，从患者患有帕金森病（PD）和设计分类/预测模型，以简化诊断。这项研究的主要目的是打开能够应用深度学习算法来帮助更好地理解和诊断疾病的可能性。据我们所知，深度学习算法的能力尚未完全用于帕金森病研究领域，我们相信通过对数据的深入理解，我们可以创建一个平台，应用不同的算法在一定程度上自动化帕金森病的诊断。我们使用Michael J. Fox Foundation提供的帕金森氏进展标志物倡议（PPMI）数据集进行分析。
In this paper, we investigate the diagnostic data from patients suffering with Parkinson’s disease (PD) and design classification/prediction model to simplify the diagnosis. The main aim of this research is to open possibilities to be able to apply deep learning algorithms to help better understand and diagnose the disease. To our knowledge, the capabilities of deep learning algorithms have not yet been completely utilized in the field of Parkinson’s research and we believe that by having an in-depth understanding of data, we can create a platform to apply different algorithms to automate the Parkinson’s Disease diagnosis to certain extent. We use Parkinson’s Progression Markers Initiative (PPMI) dataset provided by Michael J. Fox Foundation to perform our analysis.