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NHS in England to Trial AI Tool for Predicting Fatal Heart Disease Risk

by Amy

The NHS in England is set to trial an advanced artificial intelligence tool designed to assess patients’ risks of heart disease and premature death. This innovative technology, named Aire, utilizes electrocardiogram (ECG) results to identify potential heart issues that may be missed by doctors.

Aire, also known as AI-ECG risk estimation, analyzes the electrical activity of the heart recorded in ECG tests. It has the capability to detect structural problems within the heart, alerting healthcare providers to patients who may need closer monitoring, additional tests, or treatment.

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In a groundbreaking initiative, the tool will first be tested at Imperial College Healthcare NHS Trust and Chelsea and Westminster Hospital NHS Foundation Trust, with plans to expand to other hospitals later. Initial trials will recruit hundreds of patients, with potential for larger studies in the future.

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Research published in the Lancet Digital Health journal indicates that Aire can accurately predict a patient’s risk of death within a decade after an ECG in 78% of cases. The AI system was trained on a dataset of 1.16 million ECG results from 189,539 patients.

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Aire can also forecast future heart failure with 79% accuracy, serious heart rhythm issues in 76% of cases, and atherosclerotic cardiovascular disease, characterized by narrowed arteries, in 70% of instances.

Dr. Fu Siong Ng, a cardiac electrophysiologist at Imperial College London, expressed his vision for the technology. He stated, “In the next five to ten years, every ECG performed in the NHS could be processed through this model. Clinicians will not only receive diagnoses but also predictions of various health risks, allowing for early interventions.”

He added, “For example, if a patient is identified as high risk for a specific heart rhythm issue, we can implement preventive measures sooner, such as weight-loss programs or early medical treatments.”

Dr. Arunashis Sau, a British Heart Foundation clinical research fellow, emphasized the goal of using AI to enhance ECG testing. “While ECGs are common and inexpensive, the data can inform more detailed testing, improving patient management and potentially lowering risks of adverse outcomes,” he explained.

He noted a key distinction: the aim is not to replace doctors but to provide insights beyond human capability in analyzing heart traces.

As the NHS embarks on this pioneering trial, the potential for AI to revolutionize heart disease risk assessment is becoming increasingly clear.

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