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New Studies: AI Captures Electrocardiogram Patterns That Could Signal a Future Sudden Cardiac Arrest

DAIC

In a study published in Communications Medicine , David Ouyang, MD, assistant professor of Cardiology and Medicine at Cedars-Sinai, along with Chugh and fellow investigators trained a deep learning algorithm to study patterns in electrocardiograms, also known as ECGs, which are recordings of the heart’s electrical activity.

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Artificial intelligence predicts undiagnosed atrial fibrillation in patients with embolic stroke of undetermined source using sinus rhythm electrocardiograms

HeartRhythm

Artificial intelligence (AI)-enabled sinus rhythm (SR) electrocardiogram (ECG) interpretation can aid in identifying undiagnosed paroxysmal atrial fibrillation (AF) in patients with embolic stroke of undetermined source (ESUS).

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AI-based preeclampsia detection and prediction with electrocardiogram data

Frontiers in Cardiovascular Medicine

In this study, we developed artificial intelligence models to detect and predict preeclampsia from electrocardiograms (ECGs) in point-of-care settings. Early diagnosis and management of preeclampsia can improve outcomes for both mother and baby.

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Researchers achieve contactless electrocardiogram monitoring

Medical Xpress - ECG

Chen Yan and researcher Sun Qibin from the University of Science and Technology of China (USTC) achieved contactless electrocardiogram (ECG) monitoring through a millimeter-wave radar system. Recently, a team led by Prof. Their work was published in IEEE Transactions on Mobile Computing and reported by IEEE Spectrum.

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CE-482904-003 NOT READY FOR PRIME TIME: CHATGPT UNDERPERFORMS IN ELECTROCARDIOGRAM INTERPRETATION

HeartRhythm

One area of interest is the use of LLMs as an aid in the interpretation of medical data and images of electrocardiograms (ECGs). As large language models (LLM) have become popular, the use of artificial intelligence (AI) for medical diagnostics has been on the forefront of medical circles and the news.

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New electrode design promises major improvements in wearable electrocardiograms

Medical Xpress - ECG

That's why the recent and rapid rise in wearable electronic health-monitoring devices with heart rate-measuring electrocardiograms (ECG) represents a significant step forward. Nearly 200 million people around the globe have coronary heart disease, which accounts for about one in every six deaths, according to the British Heart Foundation.

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PO-03-009 RECLASSIFICATION OF THE CONVENTIONAL RISK ASSESSMENT FOR AGING-RELATED DISEASES BY ELECTROCARDIOGRAM-ENABLED BIOLOGICAL AGE

HeartRhythm

The electrocardiogram (ECG) had been used for the prediction of biological age (ECG-BA). Chronological age (CA) is a traditional powerful risk factor for aging-related diseases.