Using an onset-anchored Bayesian hierarchical model to improve predictions for amyotrophic lateral sclerosis disease progression

Using an onset-anchored Bayesian hierarchical model to improve predictions for amyotrophic lateral sclerosis disease progression

Abstract Background Amyotrophic Lateral Sclerosis (ALS), also known as Lou Gehrig’s disease, is a rare disease with extreme between-subject variability, especially with respect to rate of disease progression. This makes modelling a subject’s disease progression, which is measured by the ALS Function...

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Bibliographic Details
Main Authors: Alex G. Karanevich, Jeffrey M. Statland, Byron J. Gajewski, Jianghua He
Format: Article
Language:English
Published: BMC 2018-02-01
Series:BMC Medical Research Methodology
Subjects:
ALS
Hierarchical modelling
ALSFRS
Prediction
Pro-act
Onset-anchor
Online Access:http://link.springer.com/article/10.1186/s12874-018-0479-9

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http://link.springer.com/article/10.1186/s12874-018-0479-9

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