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CancerSymptomNetworks

This is a demo of the application of Bayesian Networks (BNs) on cancer symptoms. If you are viewing this from github you can find its html form in the following link.

Below please find attached a list of interactive Bayesian Networks, ran on the same set of cancer symptom data. The complete dataset consisted of 38 different symptoms collected from 1328 cancer patients. Inside this dataset, there were 295 male and 1033 female cancer patients. There were, also, 958 cancer patients below the age of 65 and 370 cancer patients above the age of 65.

The networks were created by the symptom dimension of occurrence. The size of nodes represent the prevalence of each symptom in our dataset, among the 1328 cancer patients. 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 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.

A. In the list below you will find the BNs created without the symptom clusters (i.e., communities) identified in the Papachristou et al. 2019. [1]

B. In the list below you will find, as a case study, the application of BNs on 4 different subgroups of cancer patients based on their gender and age (i.e., male vs female, < 65 versus > 65 years of age), without the symptom clusters (i.e., communities) identified in the Papachristou et al. 2019. [1]

C. In the list below you will find the BNs created with the symptom clusters (i.e., communities) identified in the Papachristou et al. 2019. [1] 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.

D. In the list below you will find, as a case study, the application of BNs on 4 different subgroups of cancer patients based on their and age (i.e., male vs female, < 65 versus > 65 years of age), with the symptom clusters (i.e., communities) identified in the Papachristou et al. 2019. [1]. 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.

[1] Papachristou, N, Barnaghi, P, Cooper, B, Kober, KM, Maguire, R, Paul, SM, Hammer, M, Wright, F, Armes, J, Furlong, EP, McCann, L, Conley, YP, Patiraki, E, Katsaragakis, S, Levine, JD, Miaskowski, C (2019). Network Analysis of the Multidimensional Symptom Experience of Oncology. Sci Rep, 9, 1:2258.