Hi this is 
A research was conducted at University of California, San Diego concerning heart disease patient data. The patients were identified with a heart attack from chest pain, diagnosed by EKG, high level of enzymes in their heart muscles, etc. The goal was to forecast which of these patients was at danger of dying from another heart attack within the next 30 days. The forecast would define the cure, like, whether to retain the patient in intensive care or not.
For every patient, around 100 variables were collected, including demographics, medical history and lab data. Using that data, a decision tree was constructed.
The decision tree predicted that if Blood Pressure was low (<=90), the risk of another heart attack was high (70%).
If the patient’s BP was ok, patient’s age was considered. If the age was low (<=62), then the patient’s survival was high (98%).
If the age was higher, sinus problems are considered. If sinus was normal, the odds of being alive were 89%. Otherwise, the odds of survival fell to 50%.
The percentage of correct forecast of this decision tree is 86.5%.
source : http://universityofcalifornia.edu/
