This research has been peer-reviewed. For more information on this research see: A Bayesian Network Model for Seismic Risk Analysis. Risk Analysis, 2021.

PURPOSETo address the need for more accurate risk stratification models for cancer immuno-oncology, this study aimed to develop a machine-learned Bayesian network model (BNM) for predicting outcomes ...

A study of over 6,800 patients identifies key pathways driving severe asthma exacerbation risk, highlighting roles for eosinophils, FeNO, and FEV₁.

A novel Bayesian Hierarchical Network Model (BHNM) is designed for ensemble predictions of daily river stage, leveraging the spatial interdependence of river networks and hydrometeorological variables ...

We consider Bayesian inference and propose using the multiplicative (or Chung–Lu random graph) model as a prior on the graphical space. In the multiplicative model, each edge is chosen independently ...

GAC Honda Applies for Patent on Vehicle Fault Diagnosis Based on Bayesian Networks, Enhancing Diagnostic Intuitiveness and Interpretability. GAC Honda's Innovative Technology Lead ...

We consider the joint sparse estimation of the regression coefficients and the covariance matrix for covariates in a high-dimensional regression model. Here, the predictors are both relevant to a ...