Scientists from the University of Toronto have created an AI - based system that can more accurately predict heart attacks , factoring in multiple risk factors and potentially reducing human error . The researchers said that standard models of prediction “ oversimplify ” cardiovascular disease ( CVD ) , leading to misdiagnosis . The neural network approach was tested over 10 years of trial time , correctly identifying 355 more CVD patients than human doctors and beating current guidelines by 50 % .
Scientists from the University of Nottingham 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 10 years of trial data, correctly identifying 355 more CVD patients than human doctors and beating current guidelines by 7.6%.