To try to develop a more qualitative tool,Knott and his colleagues trained an AI model to read scans and learn to detect signs of compromised blood flow.When they tested the technology on the scans of more than 1000 people who needed CMR because they either at risk of developing heart disease or had already been diagnosed,they found the AI model worked pretty well at selecting out which people were more likely to go on to have a heart attack or stroke,or die from one.The study compared the AI-based analyses to health outcomes from the patients,who were followed for about 20 months on average.The researchers discovered that for every 1 ml/g/min decrease in blood flow to the heart,the risk of dying from a heart event nearly doubled,and the risk of having a heart attack,stroke or other event more than doubled.