Exploring Best Practices for ECG Signal Processing in Machine Learning

1 code implementation • 2 Nov 2023 • Amir Salimi, Sunil Vasu Kalmady, Abram Hindle, Osmar Zaiane, Padma Kaul

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.

Multi-Label Classification

Improving ECG-based COVID-19 diagnosis and mortality predictions using pre-pandemic medical records at population-scale

no code implementations • 14 Nov 2022 • Weijie Sun, Sunil Vasu Kalmady, Nariman Sepehrvand, Luan Manh Chu, Zihan Wang, Amir Salimi, Abram Hindle, Russell Greiner, Padma Kaul

Pandemic outbreaks such as COVID-19 occur unexpectedly, and need immediate action due to their potential devastating consequences on global health.

COVID-19 Diagnosis Transfer Learning

ECG for high-throughput screening of multiple diseases: Proof-of-concept using multi-diagnosis deep learning from population-based datasets

no code implementations • 6 Oct 2022 • Weijie Sun, Sunil Vasu Kalmady, Amir Salimi, Nariman Sepehrvand, Eric Ly, Abram Hindle, Russell Greiner, Padma Kaul

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.