Cardiovascular disease prediction: a novel risk-stratification tool
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چکیده
Cardiovascular disease (CVD) accounts for 1 in 3 deaths worldwide. However, current “state-of-the-art” prediction tools annually misdiagnose 31.6 million Americans. We propose a novel risk stratification tool by applying methods of machine learning to health claims data. Our neural network outperformed the current state-of-the-art in terms of area under the curve (AUC) and illustrated that area of residence, which is currently neglected by alternative tools, is in fact one of the strongest predictors of CVD.
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