A deep learning modular ECG approach for cardiologist assisted adjudication of atrial fibrillation and atrial flutter episodes Detection of atrial tachyarrhythmias (ATA) on long-term electrocardiogram (ECG) recordings is a prerequisite to reduce ATA-related adverse events. However, the burden of editing massive ECG data is not sustainable. Deep learning (DL) algorithms provide improved performances on resting ECG databases. However, results on long-term Holter recordings are scarce.

1/ 🧠❤️🤖 New in @heartrhythmsociety.bsky.social's #HRO2 journal: a deep learning modular ECG approach for cardiologist-assisted adjudication of AF and atrial flutter. www.heartrhythmopen.com/article/S266... #ExplainableAI #DeepLearning #AFibCare #BiomedicalAI #EPeeps

Providing medical care in health resource–constrained global areas: Syria

3/ Takeaway from Dr. Uma Srivatsa's editorial:
“Prevention is key to addressing AF risk factors & reducing strain on underfunded systems.” www.sciencedirect.com/science/arti... #Cardiology #AFibCare #EPeeps