Artificial intelligence could play a pivotal role in the early diagnosis of people who are at risk of heart failure as it is able to identify anomalies which are traditionally hard to detect, new research shows.
Heart and circulatory diseases are the world’s biggest killer, claiming one in three lives every year. Researchers in Scotland set out to test how AI could have “real-world benefits” for those at risk.
Thanks to patients who voluntarily offered their data to the Scottish Health Research Register and Biobank (SHARE), researchers at the University of Dundee’s School of Medicine looked at a final cohort of 578 people to see how AI could help.
The team, whose research has been published in the journal ESC Heart Failure, used AI to interrogate population-based electronic health records and echocardiography heart scans in order to identify patients with heart failure.
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AI deep learning was then used to examine the images to identify anomalies that could increase a patient’s risk.
Professor Chim Lang said: “Our research represents an advancement in the utilisation of deep learning to automatically interpret echocardiographic images.
“This can allow us to streamline the identification of patients with heart failure at scale within electronic health record datasets.
“Echocardiography heart scans that were enhanced by the AI software helped to provide more measurements – or parameters – of heart structure and function that can be used to help diagnose heart failure.
“These measurements were not routinely reported by the usual heart scans from the electronic health records.
“When compared to reports generated by routine heart scans, those enhanced by AI were more detailed and could also be processed at a…
