Predicting the progression of Parkinson's disease using conventional MRI and machine learning: An application of radiomic biomarkers in whole‐brain white matter-Reference-Cited by-同舟云学术

Predicting the progression of Parkinson's disease using conventional MRI and machine learning: An application of radiomic biomarkers in whole‐brain white matter

Published:2020-10-05 Issue:3 Volume:85 Page:1611-1624
ISSN:0740-3194
Container-title:Magnetic Resonance in Medicine
language:en
Short-container-title:Magn. Reson. Med.

Author:

Shu Zhen‐Yu¹²^ORCID,Cui Si‐Jia³,Wu Xiao¹,Xu Yuyun²,Huang Peiyu¹,Pang Pei‐Pei⁴,Zhang Minming¹

Affiliation:

1. Department of Radiology The Second Affiliated HospitalZhejiang University School of Medicine Hangzhou Zhejiang Province China

2. Department of Radiology Zhejiang Provincial People’s HospitalAffiliated People’s Hospital of Hangzhou Medical College Hangzhou Zhejiang Province China

3. Second Clinical CollegeZhejiang Chinese Medical University Hangzhou Zhejiang Province China

4. GE Healthcare China Shanghai China

Publisher

Wiley

Subject

Radiology Nuclear Medicine and imaging

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.28522

Reference49 articles.

1. Exploring the Effects of Genetic Variants on Clinical Profiles of Parkinson’s Disease Assessed by the Unified Parkinson’s Disease Rating Scale and the Hoehn–Yahr Stage

2. Parkinson's disease

3. Prevalence, Determinants, and Effect on Quality of Life of Freezing of Gait in Parkinson Disease