Researchers from Queen Mary University of London and Barts Health NHS Trust have secured £1.3m in funding to advance a new AI system designed to improve the detection of heart failure.
The technology, known as the Intelligent Heart Evaluation Framework (iHeF), aims to help clinicians identify patients at risk earlier while reducing pressure on NHS diagnostic services.
The funding, awarded through the National Institute for Health and Care Research (NIHR) Invention for Innovation programme, will support further testing and development of the AI screening platform.
Researchers will use the investment to gather evidence needed for regulatory approval and evaluate how the technology can be integrated into routine NHS care.
If successful, the project could significantly reduce waiting times for heart failure assessments, lower healthcare costs, and improve patient outcomes by prioritising those who require urgent investigation and treatment.
The research team expects the technology could be ready for clinical use by the end of 2028.
Tackling a growing heart failure challenge
Heart failure affects more than one million people across the UK, yet hundreds of thousands of cases are believed to remain undiagnosed.
Early detection is critical because prompt treatment can improve quality of life, reduce hospital admissions, and lower the risk of serious complications.
However, diagnosing heart failure remains a resource-intensive process. Patients are commonly referred for echocardiography, an ultrasound examination that assesses the structure and function of the heart.
These scans require specialist equipment and trained staff, limiting capacity within hospitals and diagnostic centres.
Demand for cardiac imaging continues to rise. During the 2024/25 period, the NHS performed more than 1.8 million echocardiograms, yet waiting lists remained substantial, with around 150,000 patients awaiting assessment.
Many patients face delays of several weeks or even months before receiving a definitive diagnosis.
How AI screening could transform diagnosis
The new AI screening system has been developed to identify signs of heart failure using a routine electrocardiogram (ECG), a test already widely used across healthcare settings.
By analysing ECG data, the algorithm can detect patterns associated with changes in the heart’s structure and pumping ability.
Unlike echocardiography, ECG testing is relatively inexpensive, easy to perform, and does not require highly specialised operators. It can be delivered in GP surgeries, community diagnostic centres, and potentially even in patients’ homes.
Because ECG testing is already part of many diagnostic pathways, introducing AI screening would not require additional appointments or major changes to existing clinical workflows.
Instead, the technology could help clinicians determine which patients genuinely need further cardiac imaging and which are unlikely to benefit from more advanced investigations.
Reducing costs and improving efficiency
One of the major challenges facing NHS cardiac services is the high number of scans that ultimately reveal no significant findings. Current estimates suggest that only about a quarter of echocardiograms yield clinically actionable results.
This means large numbers of patients undergo costly investigations despite having no evidence of heart failure or only minor abnormalities that do not require treatment.
The financial impact is significant, with diagnostic pathways estimated to cost hundreds of millions of pounds annually.
Researchers believe AI screening could help address this inefficiency by filtering out low-risk patients before they reach specialist imaging services. This would allow hospitals to focus resources on individuals most likely to benefit from further assessment.
Three-year evaluation underway
The newly funded programme will run over the next three years and will involve direct collaboration between researchers, clinicians, technicians, and patients.
Alongside comparing iHeF with existing diagnostic standards, the team will assess how healthcare professionals use AI-generated insights and how patients respond to AI-supported decision-making.
The project will also examine the wider economic and healthcare impact of deploying the technology across the NHS.
As the population ages, heart failure cases are expected to increase, and healthcare leaders are increasingly turning to digital innovation to expand capacity.
If the upcoming trials confirm its effectiveness, iHeF could become an important new tool in heart failure detection, helping the NHS deliver faster diagnoses while making better use of limited diagnostic resources.
Team Health Accessible
Health & Wellness Editorial Team
HealthAccessible editorial team delivers trusted, accessible, and evidence-based health information for everyone.
