Абстрактный

Forecasting Diseases by Classification and Clustering Techniques

Nikita Ghiya, Samruddhi Godbole, Pooja Hol, Gayatri Deortare, Madhuri Chavan

In medical industry there is a huge amount of patients data which is not mined. This healthcare data can be used to extract knowledge for further disease prediction. Currently data mining techniques are widely used in clinical expert systems for prediction of various diseases. These techniques discover the hidden relationships and patterns of the healthcare data.No such expert system which can predict more than one disease exists till date. Almost all other systems use clinical data having parameters and inputs from the tests conducted in laboratory. Very few expert systems are based on the risk factors affecting the disease such as heart disease and diabetes. By using K-means Clustering Algorithm(KCA) in our proposed system, the disease can be predicted more accurately and in less time. Such systems will warn the people about the presence of their disease even before he concerns the doctor. This can even help doctors to carry out specific tests of the patients and target out the disease