Smart Health Care Implementation Using Naïve Bayes Algorithm (International Journal of Innovative Research in Computer Science & Technology, 2019)
Heart disease and diabetes are two most  commonly found chronic disease that has become a  mainstream health issue with the current lifestyle. It is  essential to identify the symptoms and treat the  disease at early stages. Data mining practices are used in number of applications. It is an exercise of  determining a large amount of pre-existing database  to produce new information. In health care system  data mining renders a vital role to predict the illness  with the given symptoms and classify the disease as  diabetes or heart disease. The major reason of data  mining in health care system is to evolve a new  automated tool for determining and diffusing  pertinent health care information. Here, the system is  fed with various attributes. According to those  attributes, the system compares the given symptoms  with the actual dataset and predicts the relevant  disease based on the user input. In this system, Naïve  Bayes algorithm and R tool have been used for  prediction and visualization. The goal is to develop a  cost-effective and easily accessible healthcare system  that can benefit the medical practitioners to combat  the prolonged procedures of diagnosis and faster  retrieval of results.
Keywords: Data Mining; Heart disease; Diabetes; Symptoms; Naïve Bayes algorithm and R tool