Application of decision tree as a data mining tool to predict BP systolic diastolic
Hemoglobin A1c is the most parameters for the monitoring of metabolic control of patients with diabetes mellitus. The aim of this study is to determine the reference rang of glycosylated hemoglobin (Hb A1c%) in an Iraqi population (males and females) and predict Bp systolic diastolic by using demonstrates the application of decision tree, as data mining tool, in the health care system. Data mining has the capability for classification, prediction, estimation, and pattern recognition by using health databases.