What does novel artificial intelligence score? New Delhi – 12 December 2021: A novel artificial intelligence score provides a more accurate forecast of the likelihood of patients with suspected or known coronary artery disease dying within 10 years than established scores used by health professionals worldwide. The research “‘Machine-learning score using stress CMR for death prediction in patients with suspected or known CAD’” is presented yesterday at EuroEcho 2021, a scientific congress of the European Society of Cardiology (ESC). EuroEcho 2021 took place 9 to 11 December online. Unlike traditional methods based on clinical data, the new score also includes imaging information on the heart, measured by stress cardiovascular magnetic resonance (CMR). “Stress” refers to the fact that patients are given a drug to mimic the effect of exercise on the heart while in the magnetic resonance imaging scanner. The study suggests patients with chest pain, dyspnea or risk factors for heart disease should undergo a stress CMR test “This is the first study to show that machine learning with clinical parameters plus stress CMR can very accurately predict the risk of death,” said study author Dr Theo Pezel of the Johns Hopkins Hospital, Baltimore, US. “The findings indicate that patients with chest pain, dyspnoea, or risk factors for cardiovascular disease should undergo a stress CMR exam and have their score calculated. This would enable us to provide more intense follow-up and advice on exercise, diet, and so on to those in greatest need.” What is risk stratification commonly used for? Risk stratification is commonly used in patients with, or at high risk of, cardiovascular disease to tailor management aimed at preventing heart attack, stroke and sudden cardiac death. Conventional calculators use a limited amount of clinical information such as age, sex, smoking status, blood pressure and cholesterol. This study examined the accuracy of machine learning using stress CMR and clinical data to predict 10-year all-cause mortality in patients with suspected or known coronary artery disease and compared its performance to existing scores. Dr Pezel explained: “For clinicians, some information we collect from patients may not seem relevant for risk…