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. Blood samples were collected from 100 healthy subjects (50 females and 50 females) are ranged between (20-75) years old as dataset. The reference value of HbA1c% was (5.34 + 0.67) % in female and (5.67 + 0.73) % in males. The present study found a strong relation between HbA1c % and systolic diastolic blood pressure in males whereas the relation in females no significant.