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BMJ Open|March 14, 2024
'I've never been so stressed in my life': a qualitative analysis of young adults' lived experience amidst pandemic restrictions in Prince Edward Island, CanadaGemma Postill, Michael Halpin, Claire Zanin, et al.
Plos One|October 25, 2022
Adherence of those at low risk of disease to public health measures during the COVID-19 pandemic: A qualitative studyGemma Postill, Cindy L Adams, Claire Zanin, et al.
PLOS Digital Health|July 1, 2025
Perspectives of family medicine residents on artificial intelligence for survival estimation in patients with serious illnessGemma Postill, Anglin Dent, Jill Dombroski, et al.
Digestive Diseases and Sciences|April 2, 2025
Unmet Healthcare Needs Among People with Inflammatory Bowel Disease: A Canadian Cross-Sectional Population-Representative StudyGemma Postill, James H B Im, Furong Tang, et al.
Annals of Epidemiology|March 5, 2026
Population-based clustering of co-occurring social determinants: an application of unsupervised machine learningIngrid Giesinger, Emmalin Buajitti, Arjumand Siddiqi, et al.
Journal of Burn Care & Research : Official Publication of the American Burn Association|March 11, 2026
Primary Care Attachment and Long-Term Mortality in Burn Survivors: A Population-Based Cohort StudyDarby Little, Elliott K Yee, Barbara Haas, et al.
JMIR Public Health and Surveillance|January 17, 2022
The Use of Cremation Data for Timely Mortality Surveillance During the COVID-19 Pandemic in Ontario, Canada: Validation StudyGemma Postill, Regan Murray, Andrew S Wilton, et al.
Burns : Journal of the International Society for Burn Injuries|April 8, 2026
Primary care utilization and attachment among burn survivors: A population-based matched cohort studyDarby Little, Elliott K Yee, Barbara Haas, et al.
Transfusion|July 31, 2025
Adherence to local rotational thromboelastometry recommendations in the care of trauma patients: A retrospective cohort studyVinyas Harish, Gemma Postill, Fayad Al-Haimus, et al.
Journal of Clinical Epidemiology|November 12, 2024
Sociodemographic bias in clinical machine learning models: a scoping review of algorithmic bias instances and mechanismsMichael Colacci, Yu Qing Huang, Gemma Postill, et al.
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