This profile is built from public research funding records (CIHR, NSERC and SSHRC) and PubMed. We have not imported them from a University of Toronto directory, so their courses and email address may be missing. Find their university profile.
Latest papers
Convergent parallel mixed-methods study to understand the impact of decision-making for congenital cardiac surgery patients at a tertiary paediatric hospital: a study protocol.
BMJ open · 2025
Artificial intelligence in medicine and the pursuit of environmentally responsible science.
The Lancet. Digital health · 2024
Canada's First Successful Paediatric Total Artificial Heart Implant.
CJC pediatric and congenital heart disease · 2023
Latest funding
- $125,000
Artificial Intelligence for Equitable Healthcare Delivery in Diagnostic Imaging
SSHRC · 2022 · Co-investigator
- $657,900
Using heart rhythm detection as a prototype to translate machine learning equitably and reproducibly to the point of care
CIHR · 2022 · Nominated PI
- $634,952
Equitable Child Health: Enabling broad ethical inquiry in pediatric care by understanding the parameters of social license for reuse of clinical data
CIHR · 2021 · Co-investigator
20 publications.
Convergent parallel mixed-methods study to understand the impact of decision-making for congenital cardiac surgery patients at a tertiary paediatric hospital: a study protocol.
Yin L, Pinkney S, Assadi A, Fan M, Zahiri Y, Mazwi M, Honjo O, Trbovich P
Artificial intelligence in medicine and the pursuit of environmentally responsible science.
Gaetani M, Mazwi M, Balaci H, Greer R, Maratta C
Canada's First Successful Paediatric Total Artificial Heart Implant.
Lynch A, Jeewa A, Maurich A, Mazwi M, Jean-St-Michel E, Floh A, Zaulan O, Yoo SJ, Langanecha B, Honjo O
Development and validation of a multivariable prediction model in pediatric liver transplant patients for predicting intensive care unit length of stay.
Siddiqui A, Faraoni D, Williams RJ, Eytan D, Levin D, Mazwi M, Ng VL, Sayed BA, Laussen P, Steinberg BE
AnnoDash, a clinical terminology annotation dashboard.
Xu J, Mazwi M, Johnson AEW
iCVS-Inferring Cardio-Vascular hidden States from physiological signals available at the bedside.
Ravid Tannenbaum N, Gottesman O, Assadi A, Mazwi M, Shalit U, Eytan D
The truth Hertz-synchronization of electroencephalogram signals with physiological waveforms recorded in an intensive care unit.
Goodwin AJ, Dixon W, Mazwi M, Hahn CD, Meir T, Goodfellow SD, Kazazian V, Greer RW, McEwan A, Laussen PC, Eytan D
Pitfalls and Possibilities of Ventricular Assist Device Support in Congenitally Corrected Transposition of the Great Arteries in Children.
Belfiore A, Maurich A, Honjo O, Mazwi M, Jean-St-Michel E, Deng M, Lynch A, Zaulan O, Jeewa A
Timing errors and temporal uncertainty in clinical databases-A narrative review.
Goodwin AJ, Eytan D, Dixon W, Goodfellow SD, Doherty Z, Greer RW, McEwan A, Tracy M, Laussen PC, Assadi A, Mazwi M
Relieving bronchial compression due to cardiomegaly: The role of aortopexy when left ventricular assist device support just is not enough.
Haranal M, Laks J, Cushing SL, Mazwi M, Jeewa A, Honjo O
Artificial Intelligence for Equitable Healthcare Delivery in Diagnostic Imaging
Principal investigators: Khalvati, Farzad
Keywords: Equitable Access to Healthcare ; Diagnostic Imaging; Compassionate Healthcare ; Machine Learning; Accessibility Barriers; Negative Appointment Experiences
Using heart rhythm detection as a prototype to translate machine learning equitably and reproducibly to the point of care
Principal investigators: Mazwi, Mjaye L; Goodfellow, Sebastian D
Keywords: Arrhythmia; Artificial Intelligence; Critical Care Medicine
Equitable Child Health: Enabling broad ethical inquiry in pediatric care by understanding the parameters of social license for reuse of clinical data
Principal investigators: Johnson, Alistair
Keywords: Critical Care; Data Science; Data Stewardship; Health Informatics; Reuse Of Clinical Data; Social License
Utilizing high resolution physiological data and artificial intelligence to develop a pediatric cardiac arrest prediction tool for*integration into bedside clinical practice
Principal investigators: Goldenberg, Anna
Utilizing high resolution physiological data and artificial intelligence to develop a pediatric cardiac arrest prediction tool for integration into bedside clinical practice
Principal investigators: Laussen, Peter C; Assadi, Azadeh; Goldenberg, Anna
Keywords: Artificial Intelligence; Big Data; Bioethics; Cardiac Arrest; Critical Care; Neural Networks; Pediatrics; Personalized Medicine; Prediction
From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.
Frequent collaborators
- Critical Care Medicine
- Pediatrics
- Centre for Urban Health Solutions
- Institute of Health Policy, Management and Evaluation
- Other
Co-authors at University of Toronto, colored by department. Thicker lines mean more shared papers; select anyone to open their profile and their own map.
Azadeh Assadi
Critical Care Medicine
4 shared papers, latest 2025
Emilie Jean-St-Michel
Faculty
3 shared papers, latest 2023
Christina Maratta
Pediatrics
1 shared papers, latest 2024
Anne-Marie Guerguerian
Pediatrics
1 shared papers, latest 2018
Laura Rosella
Centre for Urban Health Solutions
1 shared papers, latest 2022
Patricia Trbovich
Institute of Health Policy, Management and Evaluation
1 shared papers, latest 2025
Seema Mital
Pediatrics
1 shared papers, latest 2021
Alistair Johnson
Faculty
1 shared papers, latest 2022
Anna Goldenberg
Critical Care Medicine
1 shared papers, latest 2020
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