Disease Prediction System using Fuzzy Logic and K-means Clustering Algorithm

In health care ecosystem there is large amount of rich information database available, but they lack inadequate techniques to gain useful information from the database. This is because of improper use of techniques to discover hidden relationship between the data. Useful information can be obtained by applying various data mining techniques on the attributes. The information which is gained can be applied for accurate disease predication and a well as treatment . Various clustering algorithms are used to mine the unsupervised data that is on dataset. K-means clustering algorithm (KCA) gives highest accuracy among the other clustering algorithm. Disease can be predicted at early stages and in less time and only from the symptoms and risk factors of affecting the individual. This paper involves preprocessing techniques, fuzzy logic and KCA which increases the accuracy of our proposed system.