A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a complication that can occur late in pregnancy.
A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a complication that can occur late in pregnancy. Preeclampsia is a sudden ...
A research team funded by the National Institutes of Health (NIH) has developed a versatile machine learning model that could one day greatly expand what medical scans can tell us about disease.
Introduction: Acute coronary syndrome (ACS) is a life-threatening emergency, with occlusion myocardial infarction (OMI) requiring rapid diagnosis and treatment. The 12-lead ECG remains the primary ...
Background: Brain natriuretic peptide (BNP) is a key heart failure biomarker. Single-lead electrocardiograms (ECGs) from wearable devices offer valuable diagnostic and prognostic insights. We ...
Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...
Abstract: The electrocardiogram (ECG) is an important tool in diagnosing heart diseases. In this study, we introduce ECGNet a customized deep learning model that utilizes advanced activation functions ...
Abstract: Bundle branch block (BBB) is a cardiac disease that occurs due to the delay in the heart’s electrical activity during a heartbeat. The early detection of BBB using 12-lead electrocardiogram ...
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