Bayes Multistage Classifier and Boosted C4.5 Algorithm in Acute Abdominal Pain Diagnosis
The medical decision problem – acute abdominal pain diagnosis is presented in the paper. We use two methods of classification, which are based on a decision tree scheme. The first of them generates classifier only based on learning set. It is boosted C4.5 algorithm. The second approach is based on Bayes decision theory. This decision algorithm utilizes expert knowledge for specifying decision tree structure and learning set for determining mode of decision making in each node. The experts-physicians gave the decision tree for performing Bayes hierarchical classifier.
KeywordsBayes classifier medical diagnosis decision tree expert knowledge
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