A Dynamic Bayesian Network model for the simulation of Amyotrophic Lateral Sclerosis progression.

ABSTRACT:

Background

Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disease progressively affecting upper and lower motor neurons in the brain and spinal cord. Mean life expectancy is three to five years, with paralysis of muscles, respiratory failure and loss of vital functions being the common causes of death. Clinical manifestations of ALS are heterogeneous due to the mix of anatomic regions involvement and the variability in disease course; consequently, diagnosis and prognosis at the level of individual patient is really challenging. Prediction of ALS progression and stratification of patients into meaningful subgroups have been long-standing interests to clinical practice, research and drug development.

Methods

We developed a Dynamic Bayesian Network (DB

SUBMITTER: Zandona A 

PROVIDER: S-EPMC6471677 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature