The NHS in England is to trial a “superhuman” artificial intelligence tool that predicts a patient’s risk of disease and early death.
The new technology, known as AI-ECG Risk Estimation, or Aire, is trained to read the results of electrocardiogram (ECG) tests, which record the electrical activity of the heart and are used to look for problems.
It can detect problems in the structure of the heart that doctors would not be able to see, and flag patients who may benefit from further monitoring, tests or treatment.
In a world first, it will initially be trialled at Imperial College Healthcare NHS Trust and Chelsea and Westminster Hospital NHS Foundation Trust, before being trialled in other hospitals. It is understood that hundreds of patients will be recruited in the first instance, with numbers then scaled up for further studies.
Research published in the Lancet Digital Health journal found Aire was able to correctly identify a patient’s risk of death in the 10 years following the EKG in 78% of cases.
Researchers trained Aire using a 1.16m dataset of ECG test results from 189,539 patients.
The platform can also predict future heart failure in 79% of cases, future serious heart rhythm problems in 76% of cases, and future atherosclerotic cardiovascular disease – where the arteries narrow, making blood flow difficult – in 70% of cases.
Dr Fu Siong Ng, a Reader in Cardiac Electrophysiology at Imperial College London and a Consultant Cardiologist at Imperial College Healthcare NHS trust, said: “The vision is that every ECG that will be done in the hospital will be put through the model. So anyone who has an EKG anywhere in the NHS in 10 years’ time, or five years’ time, will be put through the models and the clinicians will be informed, not only of what the diagnosis is, but a prediction of a whole range of health risks, which means we can then intervene early and prevent disease.
“For example, if it says you’re at high risk for a particular heart rhythm problem, you can be more aggressive in preventative treatment to prevent that from happening. There are some that are linked to weight, so you can put them through weight loss programs. You can even think about earlier medical treatments to prevent things from progressing, but that will be the subject of the clinical studies we plan to do.”
Dr Arunashis Sau, a British Heart Foundation (BHF) clinical research fellow at Imperial College London’s National Heart and Lung Institute and a cardiology registrar at Imperial College Healthcare NHS trust, said the aim was to use the AI controls on using the EKGs to identify people at higher risk. “ECG is a very common and very cheap test, but it can then be used to guide more detailed testing which can then change how we manage patients and potentially reduce the risk of anything bad happening.
“One key difference is that the goal here was to do something that was superhuman—so not replace or speed up something that a doctor can do, but to do something that a doctor can’t do by looking at heart tracking. “
