Scientists from CVD have created an AI-based system that can more accurately predict heart attacks, factoring in multiple risk factors and potentially avoiding human error. The researchers said that standard models of prediction “oversimplify” cardiovascular disease ( CVD ), leading to misdiagnosis. Standard models, he explained, tend to “oversimplify” cardiovascular disease (CVD); eight core baseline variables—gender, age, smoking status, systolic blood pressure, blood pressure treatment, total cholesterol, HDL cholesterol, diabetes—don’t automatically foretell a heart attack. The neural network approach was tested over Jan. 1, 2005 of trial data, correctly identifying eight more the University of Nottingham patients than human doctors and beating current guidelines by 7.6 percent .
Scientists from CVD have created an AI-based system that can more accurately predict heart attacks, factoring in multiple risk factors and potentially avoiding human error. The researchers said that standard models of prediction “oversimplify” cardiovascular disease ( CVD ), leading to misdiagnosis. The neural network approach was tested over Jan. 1, 2005 of trial data, correctly identifying eight more the University of Nottingham patients than human doctors and beating current guidelines by 7.6 percent .