A large network meta-analysis ranked eight GLP-1 receptor agonists for glycemic, weight, and safety outcomes in adults with ...

With the rapid in global popularization, produced with the definition of the electronic evidence, concept appears. Thus cause the attention of people to electronic evidence. Electronic evidence ...

The Bayesian Networks are graphical models that are easy to interpret and update. These models are useful if the knowledge is uncertain, but they lack some means to express ambiguity. To face this ...

Network meta-analysis (NMA) is an increasingly popular statistical method of synthesising evidence to assess the comparative benefits and harms of multiple treatments in a single analysis. Several ...

Bayesian-Torch is designed to be flexible and enables seamless extension of deterministic deep neural network model to corresponding Bayesian form by simply replacing the deterministic layers with ...

Bayesian Networks operate through a process known as Bayesian inference, a statistical reasoning method. Bayesian inference uses Bayes’ theorem to update the probability of a hypothesis as more ...

Learning Bayesian networks from data involves 2 tasks: learning network structure (determining dependencies between variables; qualitative component) and learning the parameters (determining the ...

Figure 2. Bayesian network model of tree mortality in the initial case and its posterior probability. RD, relative density; N, number of trees per hectare; Age, plantation age; Gini, coefficient of ...

Methods: This LISR and network meta-analysis is maintained using a novel living evidence synthesis (LIvE) framework. The framework facilitates the identification of new or updated studies using an ...