Multilabel 12-Lead Electrocardiogram Classification Using Gradient Boosting Tree Ensemble. - Alexander William Wong; Weijie Sun 004; Sunil Vasu Kalmady; Padma Kaul; Abram Hindle (CinC, 2020)

Multilabel 12-Lead Electrocardiogram Classification Using Beat to Sequence Autoencoders. - Alexander William Wong; Amir Salimi; Abram Hindle; Sunil Vasu Kalmady; Padma Kaul (ICASSP, 2021)

Improving the Calibration of Long Term Predictions of Heart Failure Rehospitalizations using Medical Concept Embedding. - Sunil Vasu Kalmady; Weijie Sun 004; Justin A. Ezekowitz; Nowell Fine; Jonathan Howlett; Anamaria Savu; Russ Greiner; Padma Kaul (SPACA, 2021)

ECG for high-throughput screening of multiple diseases: Proof-of-concept using multi-diagnosis deep learning from population-based datasets. - Weijie Sun 004; Sunil Vasu Kalmady; Amir Salimi; Nariman Sepehrvand; Eric Ly; Abram Hindle; Russell Greiner; Padma Kaul (CoRR, 2022)

Improving ECG-based COVID-19 diagnosis and mortality predictions using pre-pandemic medical records at population-scale. - Weijie Sun 004; Sunil Vasu Kalmady; Nariman Sepehrvand; Luan Manh Chu; Zihan Wang 007; Amir Salimi; Abram Hindle; Russell Greiner; Padma Kaul (CoRR, 2022)

Supervised Electrocardiogram(ECG) Features Outperform Knowledge-based And Unsupervised Features In Individualized Survival Prediction. - Yousef Nademi; Sunil Vasu Kalmady; Weijie Sun 004; Shiang Qi; Abram Hindle; Padma Kaul; Russell Greiner (ML4H@NeurIPS, 2023)

Generative Data by β-Variational Autoencoders Help Build Stronger Classifiers: ECG Use Case. - Yousef Nademi; Sunil Vasu Kalmady; Weijie Sun 004; Amir Salimi; Abram Hindle; Padma Kaul; Russell Greiner (SIPAIM, 2023)

Exploring Best Practices for ECG Signal Processing in Machine Learning. - Amir Salimi; Sunil Vasu Kalmady; Abram Hindle; Osmar Zaïane; Padma Kaul (CoRR, 2023)

Towards artificial intelligence-based learning health system for population-level mortality prediction using electrocardiograms. - Weijie Sun 004; Sunil Vasu Kalmady; Nariman Sepehrvand; Amir Salimi; Yousef Nademi; Kevin Bainey; Justin A. Ezekowitz; Russell Greiner; Abram Hindle; Finlay A. McAlister; Roopinder K. Sandhu; Padma Kaul (npj Digit. Medicine, 2023)

Federated Learning and Differential Privacy Techniques on Multi-hospital Population-scale Electrocardiogram Data. - Vikhyat Agrawal; Sunil Vasu Kalmady; Venkataseetharam Manoj Malipeddi; Manisimha Varma Manthena; Weijie Sun 004; Md. Saiful Islam 007; Abram Hindle; Padma Kaul; Russell Greiner (ICMHI, 2024)

Federated Learning and Differential Privacy Techniques on Multi-hospital Population-scale Electrocardiogram Data. - Vikhyat Agrawal; Sunil Vasu Kalmady; Venkataseetharam Manoj Malipeddi; Manisimha Varma Manthena; Weijie Sun 004; Saiful Islam; Abram Hindle; Padma Kaul; Russell Greiner (CoRR, 2024)

Development and validation of machine learning algorithms based on electrocardiograms for cardiovascular diagnoses at the population level. - Sunil Vasu Kalmady; Amir Salimi; Weijie Sun 004; Nariman Sepehrvand; Yousef Nademi; Kevin Bainey; Justin A. Ezekowitz; Abram Hindle; Finlay A. McAlister; Russell Greiner; Roopinder K. Sandhu; Padma Kaul (npj Digit. Medicine, 2024)

Predicting COVID-19 Outcomes Among Albertans With Diabetes and COVID-19: A Machine Learning Approach. - Dean Eurich; Darren Lau; Weiting Li; Olivia R. Weaver; Tanya Joon; Ming Ye; Finlay A. McAlister; Padma Kaul; Salim Samanani (Adv. Artif. Intell. Mach. Learn., 2025)