The NHS in England is to test a ‘superhuman’ artificial intelligence tool that predicts a patient’s risk of illness and premature 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 heart’s electrical activity and are used to check for problems.
It can detect problems in the heart’s structure that doctors might not see, and flag patients who could benefit from further monitoring, testing or treatment.
In a world first, it will initially be trialled at Imperial College Healthcare NHS Trust and the Chelsea and Westminster Hospital NHS Foundation Trust, before being tested in other hospitals. It is understood that hundreds of patients will be recruited initially, with numbers then scaled up for further studies.
Research published in the journal Lancet Digital Health found that Aire was able to correctly identify a patient’s risk of death in the 10 years after the ECG in 78% of cases.
Researchers trained Aire using a dataset of 1.16m 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 done in hospital will be run through the model. So everyone who has an ECG somewhere in the NHS in ten or five years’ time will be put through the models and the doctors will be informed, not just about what the diagnosis is, but also about a prediction of a whole series. of health risks, which means we can intervene early and prevent diseases.
“For example, if it says that you are at high risk for a specific heart rhythm problem, you can be more aggressive in preventive treatment to prevent this. There are a few that are related to weight, so you can track them through weight loss programs. You could even think about previous medical treatments to prevent the situation from developing further, but that will be the subject of the clinical trials 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 improve the AI controls on the ECGs to use to identify people. higher risk. “ECG is a common and very cheap test, but it could then be used to guide more detailed tests, which could then change the way we deal with patients and potentially reduce the risk of something bad happening.
“An important distinction is that the goal here was to do something that was superhuman – so not to replace or speed up something that a doctor could do, but to do something that a doctor cannot do when looking at heart research.”
