Prediction of Diabetes in Pregnant women using Machine Learning Algorithm

Abstract

Data Mining is a popular technology employed in the area of healthcare industry. There has been a steady up rise in use of technology in the field of health care. Predictive analytics is being seen as a more suitable approach of reducing the health issues. Hence, the study of each diseases can give new way to predict the chance of happening it again which help to prevent before it happens. Use of predictive analytics in health care would provide insight on learning patterns and factors that causes diseases. The diabetes data which consists of wide range of attributes is chosen to apply well-known classifying algorithms like J48, SMO and Naïve Bayes to find the accurate result. We compare the answers gathered from the three algorithm to fetch result that is more accurate. Data mining with Classification Algorithms plays an important role in the field of medical diagnosis to diagnose the disease. There requires a model built to analyse and extract information from the data. This paper discuss about the model, which gives an accurate result to the women about chances of getting gestational diabetes according to the data given.