What You Should Know:
– Researchers at Mount Sinai have enhanced an existing artificial intelligence (AI) algorithm to provide specific numeric probabilities identifying patients at risk for hypertrophic cardiomyopathy (HCM), a common inherited heart condition,…
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What You Should Know:
– HeartBeam, a medical technology company focused on transforming cardiac care by providing powerful personalized insights, today announced a strategic collaboration with AccurKardia, an innovator in ECG-based diagnostics technology.
– The partnership…
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The COVID-19 pandemic accelerated the adoption of telehealth and remote monitoring in obstetric care. This study assessed pregnant patients’ perceptions before and after using a novel non-invasive fetal electrocardiogram (NI-FECG) device. The trial is…
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Researchers at Imperial College Healthcare NHS Trust have created an AI model which can flag female patients who are at higher risk of heart disease based on an electrocardiogram (ECG).
The team from Imperial College…
Hypertension is a major risk factor for cardiovascular disease (CVD), yet blood pressure is measured intermittently and under suboptimal conditions. We developed a deep learning model to identify hypertension and stratify risk of CVD…
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Background: Major surgery is associated with significant morbidity and a reduced quality of life, particularly among older adults and individuals with frailty and impaired functional capacity. Multimodal prehabilitation can enhance functional recovery after surgery…
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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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