A novel machine learning based framework for developing composite digital biomarkers of disease progression

A novel machine learning based framework for developing composite digital biomarkers of disease progression

BackgroundCurrent methods of measuring disease progression of neurodegenerative disorders, including Parkinson's disease (PD), largely rely on composite clinical rating scales, which are prone to subjective biases and lack the sensitivity to detect progression signals in a timely manner. Digita...

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Bibliographic Details
Main Authors: Song Zhai, Andy Liaw, Judong Shen, Yuting Xu, Vladimir Svetnik, James J. FitzGerald, Chrystalina A. Antoniades, Dan Holder, Marissa F. Dockendorf, Jie Ren, Richard Baumgartner
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Digital Health
Subjects:
composite digital biomarker
Parkinson's disease
disease progression
linear mixed effects model
machine learning
penalized generalized estimating equations
Online Access:https://www.frontiersin.org/articles/10.3389/fdgth.2024.1500811/full
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https://www.frontiersin.org/articles/10.3389/fdgth.2024.1500811/full

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