SF50. Cancer patients with age below 65 (n=958), Max-Min Hill Climbing, optimal threshold according to Scurati & Nagarajan, 2013 (with symptom clusters)

This network represents the network structure of 38 different symptoms collected from cancer patients below the age of 65. It has been realised with the Max-Min Hill Climbing Bayesian Network (BN) algorithm. This final structure was created after we ran 10.000 Bayesian Networks and used the Scutari and Nagarajan’s statistically-driven method for retaining the true edges in the final, averaged network.[1] If an edge pointed from symptom X to symptom Y in at least 51% of the networks, then this direction was depicted in the final, averaged network.

The six different colored node groups represent the symptom clusters (i.e., psychological, pain and abdominal pain, respiratory, hormonal, chemotherapy-related, nutritional) identified in the Papachristou et al., 2019. [2]

The size of nodes represent the prevalence of each symptom in our dataset. The width of the edges are proportional to the strength that symptoms connect with each other, based on the conditional probabilities identified with the BN algorithm.

By clicking on a node you can see its markov blanket, meaning the specific symptom with its parents and children. You can see the same markov blanket by selecting a symptom in the menu on the left.

You can see each symptom cluster (i.e., psychological, pain and abdominal pain, respiratory, hormonal, chemotherapy-related, nutritional) separately by selecting a cluster in the second menu on the left.

You can move each node in the diagram by click and drag. To deselect it click on the white space of the diagram. To restart the diagram refresh the page.

To see the full description of the symptoms' labels go to the bottom of the page, below the main diagram.