According to a study, artificial intelligence could potentially predict the likelihood of an individual experiencing a heart attack up to a decade in advance. Researchers at the University of Oxford believe that this technology has the potential to save numerous lives and improve treatment for nearly half of all patients.
Funded by the British Heart Foundation (BHF), the study focused on how AI could enhance the accuracy of cardiac CT scans, which are utilized to detect blockages or constrictions in the arteries. Prof. Charalambos Antoniades, the head of cardiovascular medicine at the BHF and the director of the comprehensive imaging and clinical center at Oxford, emphasized that some patients who seek medical attention for chest pain, even if initial tests show no signs of heart disease, may still be at a high risk of experiencing a heart attack within the next decade.
The research involved analyzing data from over 40,000 patients who underwent regular cardiac CT scans at eight medical institutions across the UK, with an average follow-up period of 2.7 years. Through the utilization of AI, the study successfully assessed the risk of heart attacks for an additional 3,393 patients over nearly eight years. Subsequently, AI-generated risk assessments were provided to medical professionals for 744 patients, leading to alterations in treatment plans for 45% of them.
Prof. Antoniades expressed optimism about the potential implementation of this AI tool within the NHS, aiming to prevent thousands of unnecessary heart attack-related deaths annually in the UK. The study revealed that individuals with significant artery blockages were at a higher risk of experiencing severe heart issues. However, it also highlighted that a considerable number of patients without significant blockages still faced heart problems, underscoring the importance of early detection and intervention.
Prof. Sir Nilesh Samani, the clinical director at the BHF, emphasized the significant role that AI technology could play in identifying individuals at the highest risk of potential heart attacks.
