Retrospective Study on Decision Tree Technique for Analysis of Blood Chemistry Values in Thai Patients Receiving Check–up at Songklanakarind Hospital
Keywords:
Data mining, Decision tree technique, Decision ruleAbstract
This retrospective study on decision tree technique for analysis of blood chemistry values in Thai patients receiving check–up at Songklanakarind hospital aimed (1) to develop and present a decision model for analysis of blood chemistry values in Thai patients receiving check-up and (2) to present the pattern of decision rule of health check-up from blood analysis result. The decision tree technique with ADTree algorithm, BFTree algorithm, J48 algorithm and LMT algorithm were used in the study. The independent variables included age, gender, glucose, creatinine, blood urea nitrogen, triglyceride, uric acid, aspartate aminotransferase, alanine aminotransferase, and alkaline phosphatase. The dependent variable was health diagnosis results.
The results of the research showed that the J48 algorithm was the most suitable algorithm for development of the decision model for blood chemistry analysis. The results of model performance were 76.96% accuracy, 56.38% precision and 16.75% recall. In addition, it was found that there were 10 patterns of decision rules for the diagnosis of abnormal health.
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