6 citations · 11 across the 4 of their papers we have counts for
4 papers
Exploring Best Practices for ECG Pre-Processing in Machine Learning
Amir Salimi, Sunil Vasu Kalmady, Abram Hindle +2
In this work we search for best practices in pre-processing of Electrocardiogram (ECG) signals in order to train better classifiers for the diagnosis of heart conditions. State of…
Improving ECG-based COVID-19 diagnosis and mortality predictions using pre-pandemic medical records at population-scale
Weijie Sun, Sunil Vasu Kalmady, Nariman Sepehrvand +6
Pandemic outbreaks such as COVID-19 occur unexpectedly, and need immediate action due to their potential devastating consequences on global health. Point-of-care routine assessment…
ECG for high-throughput screening of multiple diseases: Proof-of-concept using multi-diagnosis deep learning from population-based datasets
Weijie Sun, Sunil Vasu Kalmady, Amir Salimi +5
Electrocardiogram (ECG) abnormalities are linked to cardiovascular diseases, but may also occur in other non-cardiovascular conditions such as mental, neurological, metabolic and i…
Multilabel 12-Lead Electrocardiogram Classification Using Gradient Boosting Tree Ensemble
Alexander William Wong, Weijie Sun, Sunil Vasu Kalmady +2
The 12-lead electrocardiogram (ECG) is a commonly used tool for detecting cardiac abnormalities such as atrial fibrillation, blocks, and irregular complexes. For the PhysioNet/CinC…