A deep learning approach for prediction of Parkinson’s disease progression

Volume: 10, Issue: 2, Pages: 227 - 239
Published: Apr 16, 2020
Abstract
This paper proposes a deep neural network (DNN) model using the reduced input feature space of Parkinson’s telemonitoring dataset to predict Parkinson’s disease (PD) progression. PD is a chronic and progressive nervous system disorder that affects body movement. PD is assessed by using the unified Parkinson’s disease rating scale (UPDRS). In this paper, firstly, principal component analysis (PCA) is employed to the featured dataset to address...
Paper Details
Title
A deep learning approach for prediction of Parkinson’s disease progression
Published Date
Apr 16, 2020
Volume
10
Issue
2
Pages
227 - 239
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