Fig. 1
From: Symptom clusters among cancer survivors: what can machine learning techniques tell us?
Network plot high risk score analysis. Every point in the network plot represents a symptom or health determinant as defined in Table 1. The size of the points represents the amount of connections it has with other symptoms and health determinants (weighted degree centrality). The thickness of the lines represents the amount of connections between those two specific symptoms or health determinants. Symptoms and health determinants are colored based on their main cluster (the cluster in which the symptom or health determinant is most frequent), and shapes are based on their subcluster (the cluster in which the symptom or health determinant is second-most frequent, with a minimum frequency of 5)