Prognostic factors of Rapid symptoms progression in patients with newly diagnosed parkinson’s disease
作者：
Highlights：
• Introducing machine learning techniques in the search for prognostic factors of rapid progression in PD.
• Evaluate a comprehensive set of 601 baseline features as potential early prognostic factors.
• Assess PD symptoms progression rate at 2 and 4 years after baseline evaluation.
• Quantile partition analysis and quantile-independent classification frameworks are tested.
• Non-motor symptoms at early stages of PD are the main determinants for rapid progression.
摘要
•Introducing machine learning techniques in the search for prognostic factors of rapid progression in PD.•Evaluate a comprehensive set of 601 baseline features as potential early prognostic factors.•Assess PD symptoms progression rate at 2 and 4 years after baseline evaluation.•Quantile partition analysis and quantile-independent classification frameworks are tested.•Non-motor symptoms at early stages of PD are the main determinants for rapid progression.
论文关键词：Parkinson’s disease,Rapid progression,Prognostic factors,Machine learning
论文评审过程：Received 26 February 2019, Revised 7 January 2020, Accepted 13 January 2020, Available online 21 January 2020, Version of Record 30 January 2020.
论文官网地址：https://doi.org/10.1016/j.artmed.2020.101807
