Agricultural Research Institute of Ontario
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Modeling Studies: Development and Validation
William Klement, Khaled El Emam
2023 · 54 Zit.
Quality control for crowdsourcing citation screening: the importance of assessment number and qualification set size
Nassr Nama, Nick Barrowman, Katie O’Hearn et al.
2020 · 32 Zit.
Evaluating the Utility and Privacy of Synthetic Breast Cancer Clinical Trial Data Sets
Samer El Kababji, Nicholas Mitsakakis, Xi Fang et al.
2023 · 22 Zit.
Revolutionizing healthcare data analytics with federated learning: A comprehensive survey of applications, systems, and future directions
Nisha Thorakkattu Madathil, Fida K. Dankar, Marton Gergely et al.
2025 · 20 Zit.
Augmenting Insufficiently Accruing Oncology Clinical Trials Using Generative Models: Validation Study
Samer El Kababji, Nicholas Mitsakakis, Elizabeth Jonker et al.
2025 · 11 Zit.
Reporting and Methodological Observations on Prognostic and Diagnostic Machine Learning Studies
Khaled El Emam, William Klement, Bradley Malin
2023 · 5 Zit.
A double-blind, crossover, non-inferiority randomized controlled trial where primary care providers and patients compare human- and AI-generated digital health messages: the AI-CARE study protocol
Audrée Lemieux, S. Kutcher, Borris Rosnay Galani Tietcheu et al.
2025 · 1 Zit.
Reporting and Methodological Observations on Prognostic and Diagnostic Machine Learning Studies (Preprint)
Khaled El Emam, William Klement, Bradley Malin
2023 · 0 Zit.
Sample size calculation for training ensemble machine learning models on health data
Nicholas Mitsakakis, Dan Liu, Thomas Walters et al.
2026 · 0 Zit.
Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Modeling Studies: Development and Validation (Preprint)
William Klement, Khaled El Emam
2023 · 0 Zit.
A double-blind, crossover, non-inferiority randomised controlled trial where primary care providers and patients compare human-generated and AI-generated digital health messages: the AI-CARE study protocol
Audrée Lemieux, S. Kutcher, Borris Rosnay Galani Tietcheu et al.
2026 · 0 Zit.