Technology and AI are increasingly being used to improve our lives, especially in the medical field. Now, researchers at the University of Oxford have used machine learning to help estimate the health of arteries and have developed a new biomarker to predict heart disease, and prevent future heart attacks. The researchers claim it can identify people at risk five years before it strikes. The typical procedure for those with chest pain is to conduct CCTA or coronary CT angiogram -- an imaging test to check the arteries. "If there is no significant narrowing of the artery, which accounts for about 75 per cent of scans, people are sent home, yet some of them will still have a heart attack at some point in the future," the press release claims.

In research funded by the British Heart Foundation (BHF), the team developed the biomarker, or'fingerprint' – called the fat radiomic profile (FRP), using machine learning. The FRP reveals biological red flags in the perivascular space lining blood vessels which supply blood to the heart. Furthermore, the tool identifies inflammation, scarring, and changes to these blood vessels, which all indicate the chances of a heart attack in the future. Very often when an individual goes to the hospital with chest pain, a standard component of care is to have a coronary CT angiogram (CCTA). This is a scan of the coronary arteries to check for any narrowed or blocked segments.