Aging affects the 12-lead electrocardiogram (ECG) and correlates with cardiovascular disease (CVD). AI-ECG models estimate aging effects as a novel biomarker but have only been evaluated on single ECGs—without utilizing longitudinal data. We validated…
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The 12-lead electrocardiogram (ECG) is inexpensive and widely available. Whether conditions across the human disease landscape can be detected using the ECG is unclear. We developed a deep learning denoising autoencoder and systematically evaluated…
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Cardiac wall motion abnormalities (WMA) are strong predictors of mortality, but current screening methods using Q waves from electrocardiograms (ECGs) have limited accuracy and vary across racial and ethnic groups. This study aimed to…
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Leeds Teaching Hospitals NHS Trust is trialling an AI tool which helps identify people at risk of developing atrial fibrillation (AF), a condition that makes them five times more likely to have a potentially…
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Researchers at Imperial College London and Imperial College Healthcare NHS Trust have developed an AI tool which could identify people at risk of type 2 diabetes up to 10 years before they begin to…
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The NHS in England is to trial an AI tool that can predict patients’ risk of developing and worsening heart disease, and their risk of early death, using an electrocardiogram (ECG).
Researchers at Imperial College…
