A Multilingual Decision Support System for early detection of Diabetes using Machine Learning approach: Case study for Rural Indian people

More than 77 million people in India are influenced by diabetes mellitus and a significant number of them are under risk with specific complications, for instance cardiovascular failure, stroke, nerve infection, etc., The prevalence ratio of diabetes is high in urban areas due to the migration of rural people and industrialization. While considering diabetes in prosperous urban, it has become a grave anxiety among rural people also. Early diagnosis and proper therapeutic management may reduce the expenditure and mortality rate. however, the cost of early diagnosis and laboratory testing is very high. To provide a user-friendly and cost-effective system, this paper proposes a multilingual decision support system by integrating the best predictive model (among various machine learning algorithms) and clinical decision support system. The proposed system provides a user interface to assess diabetes by themselves or with a nursing assistant available in primary health centre.