Disease prediction in data mining using association rule mining and keyword based clustering algorithms

The health sector today contains hidden information that can be important in making decisions. It is difficult for medical practitioners to predict the disease as it is a complex task that requires experience and knowledge. The objective of the research is to predict possible disease from the patient data-set using data mining techniques and determines which model gives the highest percentage of correct predictions for the diagnoses. In this paper using the association rule mining algorithm for extract the matched features from the hospital information database and keyword-based clustering algorithm is used to find the accurate disease which is affected by the patient. Both the algorithms are used to obtain the accurate results with more efficiency and quick processing.