Non-motor Clinical and Biomarker Predictors Enable High Cross-Validated Accuracy Detection of Early PD but Lesser Cross-Validated Accuracy Detection of Scans Without Evidence of Dopaminergic Deficit

Non-motor Clinical and Biomarker Predictors Enable High Cross-Validated Accuracy Detection of Early PD but Lesser Cross-Validated Accuracy Detection of Scans Without Evidence of Dopaminergic Deficit

Background: Early stage (preclinical) detection of Parkinson's disease (PD) remains challenged yet is crucial to both differentiate it from other disorders and facilitate timely administration of neuroprotective treatment as it becomes available.Objective: In a cross-validation paradigm, this w...

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Bibliographic Details
Main Authors: Charles Leger, Monique Herbert, Joseph F. X. DeSouza
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-05-01
Series:Frontiers in Neurology
Subjects:
predicting Parkinson's
SWEDD
random forest
XGBoost
logistic regression
Online Access:https://www.frontiersin.org/article/10.3389/fneur.2020.00364/full

Internet

https://www.frontiersin.org/article/10.3389/fneur.2020.00364/full

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