SickKids Foundation
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
Gary S. Collins, Karel G.M. Moons, Paula Dhiman et al.
2024 · 1.814 Zit.
Do no harm: a roadmap for responsible machine learning for health care
Jenna Wiens, Suchi Saria, Mark Sendak et al.
2019 · 951 Zit.
Transparency and reproducibility in artificial intelligence
Benjamin Haibe‐Kains, George Alexandru Adam, Ahmed Hosny et al.
2020 · 487 Zit.
Ethical limitations of algorithmic fairness solutions in health care machine learning
Melissa D. McCradden, Shalmali Joshi, Mjaye Mazwi et al.
2020 · 255 Zit.
APPRAISE-AI Tool for Quantitative Evaluation of AI Studies for Clinical Decision Support
Jethro C.C. Kwong, Adree Khondker, Katherine Lajkosz et al.
2023 · 110 Zit.
A Research Ethics Framework for the Clinical Translation of Healthcare Machine Learning
Melissa D. McCradden, James A. Anderson, Elizabeth A. Stephenson et al.
2022 · 108 Zit.
Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations
Joseph Alderman, Joanne Palmer, Elinor Laws et al.
2024 · 105 Zit.
Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning
Melissa D. McCradden, Shalmali Joshi, James A. Anderson et al.
2020 · 102 Zit.
Evaluation of domain generalization and adaptation on improving model robustness to temporal dataset shift in clinical medicine
Lin Guo, Stephen Pfohl, Jason Fries et al.
2022 · 84 Zit.
Clinical research underlies ethical integration of healthcare artificial intelligence
Melissa D. McCradden, Elizabeth A. Stephenson, James A. Anderson
2020 · 84 Zit.
Systematic Review of Approaches to Preserve Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine
Lin Lawrence Guo, Stephen Pfohl, Jason Fries et al.
2021 · 80 Zit.
Ethical Considerations for Artificial Intelligence in Medical Imaging: Data Collection, Development, and Evaluation
Jonathan Herington, Melissa D. McCradden, Kathleen Creel et al.
2023 · 58 Zit.
Machine Learning and Artificial Intelligence in Pediatric Research: Current State, Future Prospects, and Examples in Perioperative and Critical Care
Hannah Lonsdale, Ali Jalali, Luis Ahumada et al.
2020 · 54 Zit.
Prevalence of abnormal cases in an image bank affects the learning of radiograph interpretation
Martin Pusic, John S. Andrews, David Kessler et al.
2012 · 54 Zit.
Ethical Considerations for Artificial Intelligence in Medical Imaging: Deployment and Governance
Jonathan Herington, Melissa D. McCradden, Kathleen Creel et al.
2023 · 51 Zit.