A Empirical study on Disease Diagnosis using Data Mining Techniques

Abstract

Data mining is an essential part in learning disclosure process where intelligent agents are incorporated for pattern extraction. In the process of developing data mining applications the most challenging and interesting task is the disease prediction. This paper will be helpful for diagnosing accurate disease by medical practitioners and analysts, portraying various data mining techniques. Data mining applications in medicinal services holds colossal potential and convenience. However the efficiency of data mining techniques on healthcare domain depends on the availability of refined healthcare data. In our current study we discuss few classifier techniques used in medical data analysis. Also few disease prediction analysis like breast cancer prediction, heart disease diagnosis, thyroid prediction and diabetic are considered. The result shows that Decision Tree algorithm suits well for disease prediction as it produces better accuracy results.