A Radiomics Approach to Predicting Parkinson’s Disease by Incorporating Whole-Brain Functional Activity and Gray Matter Structure

A Radiomics Approach to Predicting Parkinson’s Disease by Incorporating Whole-Brain Functional Activity and Gray Matter Structure

Parkinson’s disease (PD) is a progressive, chronic, and neurodegenerative disorder that is primarily diagnosed by clinical examinations and magnetic resonance imaging (MRI). In this study, we proposed a machine learning based radiomics method to predict PD. Fifty healthy controls (HC) along with 70...

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Bibliographic Details
Main Authors: Xuan Cao, Xiao Wang, Chen Xue, Shaojun Zhang, Qingling Huang, Weiguo Liu
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-07-01
Series:Frontiers in Neuroscience
Subjects:
Parkinson’s disease
radiomics
resting-state functional magnetic resonance imaging
structural magnetic resonance imaging
machine learning
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2020.00751/full

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