Results 191 to 200 of about 22,057,993 (342)
Conditional Gaussian graphical model for estimating personalized disease symptom networks. [PDF]
Xie S, McDonnell E, Wang Y.
europepmc +1 more source
ABSTRACT Objective Despite the availability of effective therapies for Multiple Sclerosis (MS), the unpredictable nature of disease progression and the variability in individual treatment outcomes call for reliable biomarkers. This pilot study aims to investigate the potential of plasma circulating microRNAs (miRNAs) as predictive biomarkers for ...
Fortunata Carbone+19 more
wiley +1 more source
Mean Field Theory for Graphical Models [PDF]
Hilbert J. Kappen, Wim J. Wiegerinck
openalex +1 more source
Timing and Predictive Value of Clinical Conditions Preceding Multiple Sclerosis in the UK Biobank
ABSTRACT Objectives Multiple sclerosis (MS) patients often experience a higher incidence of clinical conditions before diagnosis, suggesting a prodromal phase. However, their predictive value and temporal trajectories remain underexplored. We investigated these aspects using the large UK Biobank's population‐based cohort, which provided clinical ...
Andrea Nova+5 more
wiley +1 more source
Recombination Analysis Using Directed Graphical Models [PDF]
Korbinian Strimmer+2 more
openalex +1 more source
An Integrated Approach of Learning Genetic Networks From Genome-Wide Gene Expression Data Using Gaussian Graphical Model and Monte Carlo Method. [PDF]
Zhao H, Datta S, Duan ZH.
europepmc +1 more source
Objective Bayes Covariate‐Adjusted Sparse Graphical Model Selection
G. Consonni, L. La Rocca, S. Peluso
semanticscholar +1 more source
A Probabilistic Graphical Model-based Approach for Minimizing Energy Under Performance Constraints
Nikita Mishra+3 more
semanticscholar +1 more source
A Validated Model to Predict Severe Weight Loss in Amyotrophic Lateral Sclerosis
ABSTRACT Severe weight loss in amyotrophic lateral sclerosis (ALS) is common, multifactorial, and associated with shortened survival. Using longitudinal weight data from over 6000 patients with ALS across three cohorts, we built an accelerated failure time model to predict the risk of future severe (≥ 10%) weight loss using five single‐timepoint ...
David G. Lester+4 more
wiley +1 more source