Algorithm 2: Disease Prediction Algorithm (DPA)
Input	:	Testing data, Classification Rules (ClassiRule1, ClassiRule2 and ClassiRule3)
Output	:	Predicted Patient Disease (PRED)
Step 1	:	//If this attribute is a target attribute, then return the target attribute value
Step 2	:	IF(ClassiRule1.attribute = TA)
Step 3	:	PRED1 = ClassiRule1.classValue
Step 4	:	ELSE
Step 5	:	//otherwise, check which rule should follow
Step 6	:	//by comparing the attribute of the instance
Step 7	:	//with the one in the rule
Step 8	:	VAL = INS[ClassiRule1.attribute]
Step 9	:	i = 0
Step 10	:	For each ClassiRule1.attributeValues [i] from ClassiRule1.attributeValues
Step 11	:	IF (ClassiRule1.attributeValues [i] == VAL)
Step 12	:	predictTargetAttributeValue(ClassiRule1.attributes [i], INS)
Step 13	:	End IF
Step 14	:	End For
Step 15	:	End IF
Step 16	:	PRED2 = Predict Testing data using MLP classifier with ClassiRule2
Step 17	:	PRED3 = Predict Testing data using Dl4jMlpClassifier with ClassiRule3
Step 18	:	PRED = ““
Step 19	:	IF (PRED1 = PRED2)
Step 20	:	PRED = PRED1
Step 21	:	ELSE IF (PRED1 = PRED3)
Step 22	:	PRED = PRED1
Step 23	:	ELSE IF (PRED2 = PRED3)
Step 24	:	PRED = PRED2
Step 25	:	End IF
Step 26	:	return PRED