Diabetes Disease Prediction Using Machine Learning

— Data mining is known as the process of sorting through a large number of data sets to create relationships and to find patterns for solving a given problem through data analysis. Classification, Association rules, Prediction, Clustering, and Sequential patterns are some of the most important and common data mining techniques. Data mining methods are used in a wide variety of applications, also seen in the healthcare sector. Data analysis in the health care industry plays a significant role in the detection of diseases. A variety of tests would be expected from the patient to diagnose a certain disease. However, using the data mining technique, the number of tests can be minimized. These tests play a critical role in time and results. The data mining methodology has benefits and drawbacks. This paper analyses how data mining methods are used to identify various types of diseases. This paper surveyed research articles that focused primarily on predicting, diabetes, heart disease and skin cancer.