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maximum-weighted spanning tree; Abstract. 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.

Enhancing Dependence Representation of Clinical Variables based on Bayesian Networks to Assist in Thyroid Disease Diagnosis and Treatment