Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality globally. Effective management ...
Mount Sinai analysis looks at the effectiveness of electrocardiograms analyzed via deep learning as a tool for early COPD detection ...
Discover how machine learning models are revolutionizing the diagnosis of occlusion myocardial infarction (OMI) in patients with acute chest pain. Machine learning models surpass clinicians and ...
Extracting the foetal signal from the mother’s abdominal electrocardiogram is a crucial step for monitoring the health of the unborn child. (Courtesy: iStock/iTie) Researchers in Iran have used a deep ...
An artificial intelligence (AI) deep-learning algorithm interpreting preoperative ECGs can identify risk for postoperative death in those undergoing cardiac surgery, noncardiac surgery, and ...
Automated diagnosis of chronic obstructive pulmonary disease using deep learning applied to electrocardiogramsJournal: eBioMedicine ...
New machine learning model predicts cardiac arrest in ICU patients using ECG data with high accuracy
In a recent article published in Npj Digital Medicine, researchers utilized electrocardiogram (ECG) data from a large retrospective cohort to extract various heart rate variability (HRV) measures.
Atrial fibrillation occurs when action potentials fire very rapidly within the pulmonary veins or atrium in a chaotic manner. The result is a very fast atrial rate — about 400 to 600 beats per minute.
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