Researchers have developed a heart'fingerprint' to tailor personalised treatment for people at high risk of deadly heart attack. Technology developed using artificial intelligence (AI) could identify people at high risk of a fatal heart attack at least five years before it strikes, according to new research funded by the British Heart Foundation (BHF). The findings are being presented at the European Society of Cardiology (ESC) Congress in Paris and published in the European Heart Journal. Researchers at the University of Oxford have developed a new biomarker, or'fingerprint', called the fat radiomic profile (FRP), using machine learning. The fingerprint detects biological red flags in the perivascular space lining blood vessels which supply blood to the heart.

Technology developed using artificial intelligence (AI) could identify people at high risk of a fatal heart attack at least 5 years before it strikes, according to new research funded by the British Heart Foundation (BHF). The findings are being presented at the European Society of Cardiology (ESC) Congress in Paris and published in the European Heart Journal. Researchers at the University of Oxford have developed a new biomarker, or'fingerprint', called the fat radiomic profile (FRP), using machine learning. The fingerprint detects biological red flags in the perivascular space lining blood vessels which supply blood to the heart. It identifies inflammation, scarring and changes to these blood vessels, which are all pointers to a future heart attack.

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.

Artificial intelligence could be used to predict those at risk of a fatal heart attack up to five years in advance, new research has found. Experts at the University of Oxford have developed a "fingerprint", or biomarker, using machine learning. When a patient is admitted to hospital with chest pain, it's standard procedure for a coronary CT angiogram (CCTA) to be performed. If no narrowing of the arteries is detected – about 75% of cases – then the patient is sent home – yet some of them suffer a heart attack in the future. There's currently no method routinely used by doctors to spot all underlying red flags of a future heart attack.