A Dataset and Benchmarks for Atrial Fibrillation Detection from Electrocardiograms of Intensive Care Unit Patients
Research by Sarah Nassar's team from Queen's University introduces a dataset and benchmarks for detecting Atrial Fibrillation in ICU patients using ECG data. The hosts compare feature-based, standard deep learning, and ECG Foundation Models, concluding that Foundation Models offer high precision and accuracy despite the noisy environment of an ICU.