Enhancing Dependence Representation of Clinical Variables based on Bayesian Networks to Assist in Thyroid Disease Diagnosis and Treatment
Fangyuan Cao, Limin Wang · 2016
In the past few decades, a large number of data mining algorithms have been proposed to assist in the practical medical diagnosis.This paper proposes a novel algorithm, k-dependence causal forest (KCF) based on Bayesian network.The experiments conducted on the thyroid disease data set suggest the KCF model always has lower 0-1 loss and contains more conditional mutual information, which means the KCF model is suitable to assist in thyroid disease diagnosis and treatment.