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 . “This may assist the drive towards personalized medicine, by better tailoring risk management to individual patients.” 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 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 % .