Analysis of machine learning techniques predicts cardiovascular disease risk, implying potential life-saving applications.
Heart disease is a noticeable indicator of the rise of mortality rate. Deficiencies in pumping adequate blood throughout the body are the leading cause of heart disease. Major causes of mortality rate vary due to COPD disease in the world today. Prediction of cardiovascular disease is a major challenge to save lives at an early stage. It will be necessary and important to extract information from the raw medical data to predict the increasing mortality rate caused by heart diseases. Using critical data analysis by applying statistical techniques and providing correct features as input to the machine learning algorithm can predict the chances of heart attack and save many lives. Various machine learning methods are used to find out overall risk. In this paper, various machine learning techniques are applied and their comparative analysis is observed to correctly identify the CVD diseases.
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Ray et al. (2024) studied this question.
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