A new artificial intelligence (AI) neutral network can successfully detect heart failure from just one heartbeat.

This is according to researchers from the University of Surrey, whose findings could drastically improve on existing detection methods for congestive heart failure (CHF).

CHF is a chronic condition that affects the heart’s ability to pump blood around the body due to fluid buildup around the heart. The condition is progressive and has high mortality rates.

Along with researchers from the University of Warwick and the University of Florence, the team used a convolutional neutral network, particularly effective at recognising patterns in data, and used it to analyse electrocardiogram (ECG) signals from publicly available ECG datasets.

From analysing a single heartbeat from the ECGs, they were able to predict with 100% accuracy whether or not the person was experiencing heart failure using advanced signal processing and machine learning tools.

How AI could improve heart failure diagnosis

Current detection methods for CHF look at heart rate variability. While this can be effective, the method is time consuming and is often prone to errors.

How well do you really know your competitors?

Access the most comprehensive Company Profiles on the market, powered by GlobalData. Save hours of research. Gain competitive edge.

Company Profile – free sample

Thank you!

Your download email will arrive shortly

Not ready to buy yet? Download a free sample

We are confident about the unique quality of our Company Profiles. However, we want you to make the most beneficial decision for your business, so we offer a free sample that you can download by submitting the below form

By GlobalData
Visit our Privacy Policy for more information about our services, how we may use, process and share your personal data, including information of your rights in respect of your personal data and how you can unsubscribe from future marketing communications. Our services are intended for corporate subscribers and you warrant that the email address submitted is your corporate email address.

The new detection method improves on this, while also identifying certain features of the ECG that indicate the severity of the condition.

Dr Pecchia, President of the European Alliance for Medical and Biological Engineering, explains what the findings could mean for those with the condition:

“With approximately 26 million people worldwide affected by a form of heart failure, our research presents a major advancement on the current methodology.

“Enabling clinical practitioners to access an accurate CHF detection tool can make a significant societal impact, with patients benefitting from early and more efficient diagnosis and easing pressures on NHS resources.”

AI as a medical tool

The use of AI and machine learning in the detection of medical conditions is a growing area in the field of diagnostics.

Recently, Cognetivity Neurosciences announced that it had developed an AI-based test to detect very early signs of dementia.

Earlier this week, the UK government announced that it was investing over £130m in new tech to tackle cancer and other debilitating illnesses, with £50m being invested in diagnostics, including the use of AI.


Read more: Artificial intelligence is making tech companies the new healthcare giants