| Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension X Liu, SC Rivera, D Moher, MJ Calvert, AK Denniston, H Ashrafian, ... The Lancet Digital Health 2 (10), e537-e548, 2020 | 452 | 2020 |
| Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension SC Rivera, X Liu, AW Chan, AK Denniston, MJ Calvert, H Ashrafian, ... The Lancet Digital Health 2 (10), e549-e560, 2020 | 373 | 2020 |
| What clinicians want: contextualizing explainable machine learning for clinical end use S Tonekaboni, S Joshi, MD McCradden, A Goldenberg Machine learning for healthcare conference, 359-380, 2019 | 273 | 2019 |
| Ethical limitations of algorithmic fairness solutions in health care machine learning MD McCradden, S Joshi, M Mazwi, JA Anderson The Lancet Digital Health 2 (5), e221-e223, 2020 | 88 | 2020 |
| Ambiguous identities of drugs and people: a scoping review of opioid-related stigma MD McCradden, D Vasileva, A Orchanian-Cheff, DZ Buchman International Journal of Drug Policy 74, 205-215, 2019 | 72 | 2019 |
| Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI B Vasey, M Nagendran, B Campbell, DA Clifton, GS Collins, S Denaxas, ... Nature medicine 28 (5), 924-933, 2022 | 61 | 2022 |
| Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning MD McCradden, S Joshi, JA Anderson, M Mazwi, A Goldenberg, ... Journal of the American Medical Informatics Association 27 (12), 2024-2027, 2020 | 45 | 2020 |
| Ethical concerns around use of artificial intelligence in health care research from the perspective of patients with meningioma, caregivers and health care providers: a … MD McCradden, A Baba, A Saha, S Ahmad, K Boparai, P Fadaiefard, ... Canadian Medical Association Open Access Journal 8 (1), E90-E95, 2020 | 33 | 2020 |
| Clinical research underlies ethical integration of healthcare artificial intelligence MD McCradden, EA Stephenson, JA Anderson Nature Medicine 26 (9), 1325-1326, 2020 | 30 | 2020 |
| A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI V Sounderajah, H Ashrafian, S Rose, NH Shah, M Ghassemi, R Golub, ... Nature medicine 27 (10), 1663-1665, 2021 | 27 | 2021 |
| A research ethics framework for the clinical translation of healthcare machine learning MD McCradden, JA Anderson, E A. Stephenson, E Drysdale, L Erdman, ... The American Journal of Bioethics 22 (5), 8-22, 2022 | 26 | 2022 |
| Conditionally positive: a qualitative study of public perceptions about using health data for artificial intelligence research MD McCradden, T Sarker, PA Paprica BMJ open 10 (10), e039798, 2020 | 22 | 2020 |
| Staying true to Rowan’s Law: how changing sport culture can realize the goal of the legislation MD McCradden, MD Cusimano Canadian Journal of Public Health 110 (2), 165-168, 2019 | 11 | 2019 |
| Concussions in sledding sports and the unrecognized “sled head”: a systematic review MD McCradden, MD Cusimano Frontiers in neurology 9, 772, 2018 | 11 | 2018 |
| Determining the unmet needs of patients with intracranial meningioma—a qualitative assessment A Baba, MD McCradden, J Rabski, MD Cusimano Neuro-Oncology Practice 7 (2), 228-238, 2020 | 9 | 2020 |
| Decide-AI expert group the. Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: Decide-ai B Vasey, M Nagendran, B Campbell, DA Clifton, GS Collins, S Denaxas, ... Nature Medicine 28 (5), 924-933, 2022 | 7 | 2022 |
| The point‐of‐care use of a facial phenotyping tool in the genetics clinic: An ethics tête‐a‐tête MD McCradden, E Patel, L Chad American Journal of Medical Genetics Part A 185 (2), 658-660, 2021 | 6 | 2021 |
| Ethics methods are required as part of reporting guidelines for artificial intelligence in healthcare V Sounderajah, MD McCradden, X Liu, S Rose, H Ashrafian, GS Collins, ... Nature Machine Intelligence 4 (4), 316-317, 2022 | 5 | 2022 |
| What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use.’ArXiv 2019 S Tonekaboni, S Joshi, MD McCradden, A Goldenberg arXiv preprint arXiv:1905.05134, 1905 | 5 | 1905 |
| When your only tool is a hammer: ethical limitations of algorithmic fairness solutions in healthcare machine learning M McCradden, M Mazwi, S Joshi, JA Anderson Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 109-109, 2020 | 4 | 2020 |
