Figure 1
From: A hidden Markov model for lymphatic tumor progression in the head and neck
Bayesian network for modelling lymphatic metastatic spread as described by (Pouymayou et al.)31. It consists of the primary tumor \(T\), hidden binary variables \(X_{v}\) for the involvement of LNL \(v\) (white circles) and observed (or diagnostic) variables as dark circles (\(Z_{v}^{{\mathcal{O}}}\), where \({\mathcal{O}}\) denotes the used diagnostic modality). There are potentially many observations per hidden variable. Annotated arcs depict the direction of lymphatic flow where the parameter next to it (\(b\) and \(t\)) represents the probability of metastatic spread. Not annotated arrows connect the LNLs to their diagnoses via sensitivity and specificity.
