Design and Development of a Heart Attack Prediction Application Using Machine Learning

Heart attacks have been a leading cause of mortality around the globe, contributing towards premature deaths. The burden of this disease has been significantly impacted due to the late deduction of the disease. Machine learning has been used to curb the late deduction issue by implementing models in technologies such as websites, software and mobile applications. However, the major challenge lies in developing technology which is widely used for practical applications. Most machine learning applications remain in the prototype stage and are not generally accepted in real-world practice. This paper defines the necessary methodologies to design and develop a machine learning-based application which is acceptable in the real world using the design science research methodology to predict heart attacks.