Data analytics in healthcare

The aim of this research is to predict the diabetic polyneuropathy, using data mining methods on the data set of patients who visit clinics due to diabetes related complaint. The data set used in the research was obtained from Bilecik State Hospital. Variables in the data set were determined by examining the patients' electronic medical records, complaints, diagnosis, and anemnia (disease history). Data set was analyzed by classification algorithms. In this manner, the data set was divided into two part: random training and test varible set. Model was built by the training data sets and tested by the test data sets. Different models was created and applied by k-Nearest Neighbors algorithm, Naive Bayes classifier, Logistic regression, C4.5 decision tree algorithm and Association rules. R programming in RStudio was used for data analyzes.