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Cardiovascular diseases (CVDs) are the number 1 cause of death globally, taking an estimated17.9 million lives each year, which accounts for 31. Heart failure is a common event caused by CVDs and this dataset contains 12 features that can be used to predict mortality by heart failure. Most cardiovascular diseases can be prevented by addressing behavioural risk factors such as tobacco use, unhealthy diet and obesity, physical inactivity and harmful use of alcohol using population-wide strategies. People with cardiovascular disease or who are at high cardiovascular risk (due to the presence of one or more risk factors such as hypertension, diabetes, hyper lipidaemia or al-ready established disease) need early detection and management where in a machine learning model can be of great help

MATLAB 100.00%
machine-learning decision-trees cardiovascular-diseases heart-failure matlab

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I'm Özlem, Sr. QA Engineer from Antalya, Turkey

Currently working as:
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