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Predictive Modelling for Chronic Disease: Machine Learning Approach

Chronic diseases are responsible for half of annual mortality (51%) and almost half of the burden of all diseases (41%) in Bangladesh. Developing countries like Bangladesh are in a probable state of approximate loss of $7.3 trillion due to chronic diseases by 2025. Healthcare industries in Bangladesh now generate, collect, and store large amount of data. With the emergence of big data analytics, the approach to determine the factors causing specific effects on health is increasingly based on machine learning techniques. Therefore, it is important to conduct a predictive big data analysis using machine learning techniques to understand the likelihood of chronic diseases, specifically diabetes, hypertension, and heart diseases that are caused by age, income, and years of diseases. The aim of this research is to develop a predictive analytics tool for chronic diseases using machine learning techniques. The application of machine learning in the healthcare sector can minimize the costs of treatment and can help in taking proactive actions.