AI Tool Poised to Revolutionize Heart Attack Prevention

A groundbreaking AI tool developed by researchers at the University of Oxford, with funding from the British Heart Foundation, has the potential to transform the prevention of deadly heart attacks. This innovative technology can accurately predict an individual's 10-year risk of having a fatal heart attack, enabling doctors to intervene early and reduce the risk of these catastrophic events.

The AI tool analyzes data from cardiac CT scans, commonly used to assess chest pain, identifying subtle changes in the fat surrounding the arteries. These changes, often overlooked by traditional methods, can provide crucial insights into a patient's risk of heart attack. In a first-in-human trial, the AI tool was able to independently and accurately predict the risk of cardiac events, including heart attacks and cardiac deaths.

Professor Charalambos Antoniades, commented that the AI tool holds the potential to revolutionize the approach to treating patients with chest pain. He noted that by identifying individuals at a heightened risk of a heart attack, the tool enables the implementation of preventative measures tailored to reduce their risk.

The researchers employed a recently developed AI tool and trained to utilize data related to alterations in inflamed arteries to indicate the early events of a heart attack. Through subsequent assessments involving an additional 3,393 patients over a span of 7.7 years, the AI tool demonstrated the capacity to autonomously and precisely forecast the likelihood of cardiac events.

The researchers are currently working to refine the AI tool and prepare it for clinical implementation across NHS, helping prevent thousands of avoidable deaths from heart attacks every year in the UK.

Professor Sir Nilesh Samani, who serves as the Medical Director at the British Heart Foundation, emphasized the significance of this study. He highlighted the potential of technology based on artificial intelligence in enhancing the identification of individuals at higher risk of future heart attacks. This, in turn, can assist clinicians in making more informed treatment decisions for their patients.