Assessment of Bayesian Network Classifiers as Tools for Discriminating Breast Cancer Pre-diagnosis Based on Three Diagnostic Methods

摘要

In recent years, a technique known as thermography has been again seriously considered as a complementary tool for the pre-diagnosis of breast cancer. In this paper, we explore the predictive value of thermo-graphic atributes, from a database containing 98 cases of patients with suspicion of having breast cancer, using Bayesian networks. Each patient has corresponding results for different diagnostic tests: mammography, thermography and biopsy. Our results suggest that these atributes are not enough for producing good results in the pre-diagnosis of breast cancer. On the other hand, these models show unexpected interactions among the thermographical attributes, especially those directly related to the class variable.