The NHS in England is to trial a “superhuman” artificial intelligence tool that predicts a patient’s risk of disease and dying early.
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 check 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 tested in other hospitals. It is understood 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 could 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 could 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 every ECG that will be done in hospital will be put through the model. So anyone who has an ECG anywhere in the NHS in 10 years’ time, or five years’ time, would be put through the models and the clinicians will be informed, not just about what the diagnosis is, but a prediction of a whole range of health risks, which means that we can then intervene early and prevent disease.
“If, for example, it says you’re at high risk of a specific heart rhythm problem, you could be more aggressive in preventative treatment to prevent it from happening. There are some linked to weight, so you can put them through weight-loss programmes. You might even think about earlier medical treatments to prevent things from progressing, but that will be the subject of the clinical studies that 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 goal was to use the AI checks on the ECGs to identify people at higher risk. “ECG is a very common and very cheap test, but that could then be used to guide more detailed testing that could then change how we manage patients and potentially reduce the risk of anything bad happening.
“One key distinction is that the goal here was to do something that was superhuman – so not replace or speed up something that a doctor could do, but to do something that a doctor cannot do from looking at heart tracing.”