Classification and development of tool for heart diseases (MRI images) using machine learning

Heart diseases are one of the major killers worldwide. Early detection of heart disease such as Global Hypokinesia can reduce this global burden. Computational method has potential to predict disease in early stages automatically and especially helpful in resources limited countries. Computational method to predict global hypokinesia based on confirms cases of global hypokinesia through MRI was developed. Almost all feature extraction method was used on MRI images and model was generated on merged and different images separately. High accuracy of model independent test set justified our approaches and reliability of model. The newly developed was implemented in python and available for open use.