Artificial intelligence (AI) is paving the way for advancements in cardiology, with researchers now able to identify patients at risk of severe arrhythmias that could trigger cardiac arrest and sudden death. According to a new study set to be published in the European Heart Journal, AI-driven algorithms have demonstrated remarkable accuracy in predicting these life-threatening conditions.

A team of scientists from Inserm, Paris Cite University, and the Paris Public Hospitals group (AP-HP), in collaboration with US researchers, developed an artificial neural network that mimics human brain functions. Their objective was to improve early detection and prevention of sudden cardiac death, a condition responsible for over 5 million fatalities worldwide each year.

The study involved analyzing data from over 240,000 ambulatory electrocardiograms (ECGs) collected from six countries, including the USA, France, the UK, South Africa, India, and Czechia. The AI algorithm processed millions of hours of heartbeat data, identifying subtle electrical signals that indicate a heightened risk of arrhythmia. Researchers focused on the time required for heart ventricles to electrically activate and relax during a complete cardiac cycle, a critical factor in assessing heart health.

Dr Laurent Fiorina, a researcher at the Paris Cardiovascular Research Centre (PARCC), explained, "By examining a patient's electrical heart signals for 24 hours, we discovered that AI could identify individuals susceptible to developing a severe arrhythmia within two weeks. Without timely intervention, such conditions could escalate to fatal cardiac arrest."

The AI model demonstrated impressive results, accurately detecting at-risk patients in over 70 per cent of cases while correctly identifying no-risk individuals with 99.9 per cent accuracy. Though still under evaluation, the technology shows promise in significantly improving arrhythmia anticipation and prevention.

This breakthrough study was conducted in collaboration with engineers from Cardiologs, a subsidiary of the Philips Group, and experts from Paris Cité University and Harvard. By leveraging AI, the researchers were able to identify warning signs previously undetectable using conventional methods.

If further validated, this AI-based model could transform cardiac monitoring. The algorithm may soon be integrated into hospital monitoring systems, enabling continuous surveillance of at-risk patients. Further, advancements in wearable technology could see its application in ambulatory Holter monitors, which track blood pressure fluctuations, and even smartwatches, offering real-time risk assessments for users.

Moving forward, the research team aims to conduct clinical trials to evaluate the AI model's effectiveness under real-world conditions. If proven successful, this innovative technology could help revolutionize cardiac care, providing early warnings and saving countless lives by enabling timely medical interventions.

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