Eriko Hoshino ¹², Ingrid van Putten ¹³, Wardis Girsang ⁴, Budy P. Resosudarmo ⁵, Satoshi Yamazaki ²³, A Bayesian belief network model for community-based coastal resource management in the Kei Islands ...

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

To 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 in ...

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 developed TransPRECISE (personalized cancer-specific integrated network estimation model), a multiscale Bayesian network modeling framework, to analyze the pan-cancer patient and cell line ...

In this study, the advanced method of a Bayesian network (BN) is used for the predictive modeling of seafarer injuries for its interpretative power as well as predictive capacity.

Using data from 3,380 adult and pediatric patients accounting for all common genotypes of sickle cell disease, researchers developed a predictive model of disease severity, using Bayesian network ...

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

In this paper, we describe Bayesian cross-validation, which provides tools for model selection and evaluation. We describe the Bayesian predictive information criterion and a Bayesian approximation to ...

The $1.3 trillion asset manager will publish a paper later this year detailing how measuring network effects helps it better ...