ECG-Based Deep Learning Framework to Identify Ventricular Arrhythmias in Patients Monitored with MCT
Ventricular Arrhythmias (VA), including Ventricular Tachycardia, Ventricular Fibrillation, and Ventricular Flutter, are life-threatening arrhythmias that can lead to sudden cardiac death. A [...]
This study aims to identify if cardiac monitoring with a 30-day MCT patch provides better patient outcome than with the 24-hr Holter. To do so, we compared the arrhythmia and ectopy diagnostic [...]
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This study suggests that long-term outpatient monitoring can provide better diagnosis, especially for patients at a higher risk of developing critical arrhythmias. Read full abstract here.
HFSA abstract study demonstrating the efficacy of the ZywieAI® algorithm in detecting episodes of sustained and/or non-sustained WCTs like ventricular tachycardia, ventricular flutter, and [...]
Atrial fibrillation (AF) is one of the most common cardiovascular problems, and its asymptomatic tendency makes AF detection challenging. Machine and deep learning methods are commonly used in AF [...]