Search Results for author:
Found 4 papers, 1 papers with code
Exploring Best Practices for ECG Signal Processing in Machine Learning
In this work we apply down-sampling, normalization, and filtering functions to 3 different multi-label ECG datasets and measure their effects on 3 different high-performing time-series classifiers.
Improving ECG-based COVID-19 diagnosis and mortality predictions using pre-pandemic medical records at population-scale
Pandemic outbreaks such as COVID-19 occur unexpectedly, and need immediate action due to their potential devastating consequences on global health.
ECG for high-throughput screening of multiple diseases: Proof-of-concept using multi-diagnosis deep learning from population-based datasets
Electrocardiogram (ECG) abnormalities are linked to cardiovascular diseases, but may also occur in other non-cardiovascular conditions such as mental, neurological, metabolic and infectious conditions.
Multilabel 12-Lead Electrocardiogram Classification Using Gradient Boosting Tree Ensemble
The 12-lead electrocardiogram (ECG) is a commonly used tool for detecting cardiac abnormalities such as atrial fibrillation, blocks, and irregular complexes.
