Conference Papers

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    Cardiovascular Disease Prediction Using Machine Learning
    (Institute of Electrical and Electronics Engineers Inc., 2022) Prajwal, K.; Tharun, K.; Navaneeth, P.; Anand Kumar, M.
    As the human population increases, so is the chance of getting diseases. There are many illnesses globally, and one of the biggest problems faced by the hospital systems today is the lack of technology to know when the patients are ill. One such illness is Cardiovascular Disease or CVD. It refers to any heart disease, vascular disease, or blood vessel disease. According to WHO, more people die of CVD's worldwide than any other cause. It affects the low and middle-income countries more. It is very hard for people living alone to contact the hospital when they are sick. Therefore, we have developed a model that can detect when a patient is ill and report back to the hospital. The system currently only identifies patients with heart disease and reports back to the hospital. We decided to go with heart disease identification because it is one of the most deadly diseases, and the risk of patients dying because of heart disease is high. Predicting whether a patient has heart disease or not is very clearly a classification problem. Therefore, we have used five models to classify. We take several factors such as blood sugar level, age, cholesterol level, and many more and give the outcome based on the input. © 2022 IEEE.
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    Critical Review on Heart Disease Prediction: A Machine Learning Approach
    (Institute of Electrical and Electronics Engineers Inc., 2023) Mahapatro, S.R.; Mahapatra, R.K.; Shet, N.S.V.; Prusty, S.B.; Satapathi, G.S.; Manjukiran, B.; Reddy, G.; Chandana, O.; Divya, N.; DImri, P.
    The heart is the second-most significant organ in the human body after the brain, which is the most significant organ. All of the body's organs are nourished and the blood is circulated. In the medical field, it might be difficult to anticipate the development of heart diseases. Data analytics is crucial for developing predictions based on new information, and it helps hospitals predict diseases. Every year, cardiovascular diseases account for more than 31 % of all fatalities globally. Different Machine learning algorithms are in this paper to predict heart disease. It presents a general overview of the previous work and offers insight into the current algorithm. © 2023 IEEE.