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. Author manuscript; available in PMC: 2017 Jun 1.
Published in final edited form as: J Biomed Inform. 2016 Mar 16;61:119–131. doi: 10.1016/j.jbi.2016.03.009

Figure 3.

Figure 3

The graphical model for our Bayesian network for CV risk prediction. Nodes represent input variables and edges represent conditional dependencies between the variables. The edge between subgraphs indicates an edge from every node in the source subgraph to every node in the destination subgraph or node. That is, the outcome variable (Event) is connected to every node in the graph. Features in the same nodes indicate those features are modeled jointly. The full description of each of the features appears in Section 5.1.