Researchers developed an AI model to detect myocardial ischemia and coronary microvascular and vasomotor dysfunction using ...
Mount Sinai analysis looks at the effectiveness of electrocardiograms analyzed via deep learning as a tool for early COPD detection ...
Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality globally. Effective management ...
Automated diagnosis of chronic obstructive pulmonary disease using deep learning applied to electrocardiogramsJournal: eBioMedicine ...
The electrocardiogram (ECG) is an important tool for exploring the structure and function of the heart due to its low cost, ease of use, efficiency, and non-invasive nature. With the rapid development ...
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 ...
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 ...
Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...
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