Featured Publications

Featured Publications

DeepRV central figure

DeepRV

Fatima Zahra Fawzi, MSc, Istok Menkovic, MD, Nicolas Dostie, MD, Maxime Tremblay-Gravel, MD, MSc, Marie-Claude Parent, MD, Gabriel Assolo, MD, Jean-François Tanguay, MD, PhD, Guillaume Marquis-Gravel, MD, MSc, Minhaj Ansari, MSc, Joshua P. Barrios, PhD, Geoffrey H. Tison, MD, MPH, Jacques Delfrate, MSc, Robert Avram, MD

Right ventricular systolic function (RVSF) is a critical determinant of cardiovascular outcomes, yet rapid assessment during coronary angiography remains challenging when prior imaging is unavailable. DeepRV is an open-weight video-based deep learning model that predicts RVSF directly from routine coronary angiograms, enabling real-time RV dysfunction screening in the cath lab.

April 27, 2026

Alexis Nolin-Lapalme, Achille Sowa, Jacques Delfrate, Olivier Tastet, Denis Corbin, Merve Kulbay, Derman Ozdemir, Marie-Jeanne Noël, François-Christophe Marois-Blanchet, François Harvey, Surbhi Sharma, Minhaj Ansari, I-Min Chiu, Valentina D'souza, Sam F. Friedman, Michaël Chassé, Brian J. Potter, Jonathan Afilalo, Pierre Adil Elias, Gilbert Jabbour, Mourad Bahani, Marie-Pierre Dubé, Patrick M. Boyle, Neal A. Chatterjee, Joshua Barrios, Geoffrey H. Tison, David Ouyang, Mahnaz Maddah, Shaan Khurshid, Julia Cadrin-Tourigny, Rafik Tadros, Julie Hussin, Robert Avram

The 12-lead electrocardiogram (ECG) remains a cornerstone of cardiovascular diagnostics, with over 300 million performed annually worldwide. Existing AI solutions for automated interpretation often lack generalizability, remain closed source, and depend on supervised learning requiring extensive labelled datasets.

January 23, 2026

Pascal Thériault-Lauzier, M.D., Ph.D. , Nils Perrin, M.D., M.Sc., Arash Sarshoghi, B.Sc., Stella Ly, Michael Knafo, Aurélie Grandchamp , Yan Xu Rong, Marie-Gabrielle Lessard, R.N., Denis Corbin, B. Eng, M.Sc., Bahareh Taji, B. Eng., Ph.D., Olivier Tastet, M.Sc., Aun Yeong Chong, M.D., Michael Froeschl, M.D., M.S., Alexander Dick, M.D., Marino Labinaz, M.D., Christopher Glover, M.D., Michel Le May, M.D., Zeeshan Ahmed, M.D., Omar Abdel-Razek, M.D., M.S., ...Pietro Di Santo, M.D., Ph.D., David Messika-Zeitoun, M.D., Ph.D., Geoffrey H. Tison, M.D., M.P.H., Juan Russo, M.D., Guillaume Marquis-Gravel, M.D., M.Sc., Jean-François Tanguay, M.D., Richard Gallo, M.D., Quoc Hung Ly, M.D., Anita Asgar, M.D., Serge Doucet, M.D., Gilbert Gosselin, M.D., Jean Grégoire, M.D., Reda Ibrahim, M.D., Philippe L. L’allier, M.D., Mohamed Nosair, M.D., Derek Y.F. So, M.D., M.Sc., and Robert Avram, M.D., M.S.

Accurate left ventricular ejectionfraction (LVEF) assessment is crucial in acute coronary syndrome (ACS)management but traditional methods like echocardiography (TTE) andventriculography have limitations such as risks, contrast exposure, andlogistical delays.The CathEF study introduced adeep-learning algorithm integrated with the PACS-AI (www.pacsai.co) platform,providing real-time LVEF estimates directly from routine coronary angiographyvideos, without extra catheterization or contrast.

Gilbert Jabbour, Alexis Nolin-Lapalme, Olivier Tastet, Denis Corbin, Paloma Jordà, Achille Sowa, Jacques Delfrate, David Busseuil, Julie Hussin, Marie-Pierre Dubé, Jean-Claude Tardif, Léna Rivard, Laurent Macle, Julia Cadrin-Tourigny, Paul Khairy, Robert Avram*, Rafik Tadros*

Atrial fibrillation is the most common sustained cardiac arrhythmia in adults and is associated with an increased risk of stroke, heart failure, cognitive decline, hospitalisations, and death. Deep learning applied to electrocardiograms (ECG-AI) is an emerging approach for predicting atrial fibrillation or flutter (AF). We introduce an open-weights ECG-AI model developed at the Montreal Heart Institute (MHI) and externally validated using MIMIC-IV dataset, comparing its performance with clinical and AF polygenic scores (PGS).

August 30, 2024

Élodie Labrecque Langlais, Denis Corbin, Olivier Tastet, Ahmad Hayek, Gemina Doolub, Sebastián Mrad, Jean-Claude Tardif, Jean-François Tanguay, Guillaume Marquis-Gravel, Geoffrey H. Tison, Samuel Kadoury, William Le, Richard Gallo, Frederic Lesage & Robert Avram

Coronary artery disease involves the narrowing of heart blood vessels of the heart, also known as. stenoses, and stands as a major global cause of mortality, requiring accurate evaluation for effective treatment. The existing gold standard for assessing stenosis severity, which relies on visual interpretation of coronary angiography videos by cardiologists, shows significant variability, highlighting the necessity for standardized, objective methods. AI-based algorithms have been developed to overcome this issue, but these methods have inherent limitations which are addressed with DeepCoro.

Robert Avram, Jeffrey E. Olgin, Zeeshan Ahmed, Louis Verreault-Julien, Alvin Wan, Joshua Barrios, Sean Abreau, Derek Wan, Joseph E. Gonzalez, Jean-Claude Tardif, Derek Y. So, Krishan Soni & Geoffrey H. Tison

Coronary heart disease (CHD) is the leading cause of adult death worldwide. The minimally-invasive procedure called coronary angiography provides the primary gateway for nearly all CHD diagnosis and clinical management decisions, as well as stent-based therapy for CHD.

October 22, 2023

Robert Avram, Joshua P Barrios, Sean Abreau, Cheng Yee Goh, Zeeshan Ahmed, Kevin Chung, Derek Y So, Jeffrey E Olgin, Geoffrey H Tison

A team of researchers at UCSF developed a technology called CathEF that uses artificial intelligence (AI) to assess how well the heart pumps blood during a common heart test.