Geographical Clustering of Cancer Incidence by Means of Bayesian Networks and Conditional Gaussian Networks
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, PMLR R3:237-242, 2001.
With the aim of improving knowledge on the geographical distribution and characterization of malignant tumors in the Autonomous Community of the Basque Country (Spain), age-standardized cancer incidence rates of the 6 most frequent cancer types for patients of each sex between 1986 and 1994 are analyzed, in relation to the towns of the Community. Concretely, we perform a geographical clustering of the towns of the Community by means of Bayesian networks and conditional Gaussian networks. We present several maps that show the clusterings encoded by the learnt models. In addition to this, we outline the cancer incidence profile for each of the obtained clusters.