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Melissa McCradden

Title: Associate Scientist
Designations: PhD, M.HSc.
Pronouns: she/her
Phone: 416-813-8841
Alternate Contact Name: Chelsea Mopas
Alternate Phone: 416-813-8980
Alternate Email:
U of T Positions: Assistant Professor, Division of Clinical and Public Health in the Dalla Lana School of Public Health

Hospital Positions

Bioethicist, Department of Bioethics
John and Melinda Thompson Director of Artificial Intelligence in Medicine

U of T Positions



Dr. McCradden is a Bioethicist with the Department of Bioethics at The Hospital for Sick Children (SickKids), providing clinical and organization ethics consultations, policy, education, and research at SickKids. She is the John and Melinda Thompson Director of Artificial Intelligence in Medicine (AIM) where, as the Integration Lead for AIM, she provides organizational guidance on responsible integration of clinical AI systems impacting patient care. Dr. McCradden holds a PhD in Neuroscience (McMaster University) and a M.HSc. in Bioethics (University of Toronto). She was the inaugural Ethics of AI in Healthcare Postdoctoral Fellow co-sponsored by SickKids and Vector Institute for Artificial Intelligence. Her work is recognized internationally and she sits on a number of external groups, including the World Health Organization’s Clinical Evaluation Working Group, and multiple reporting guideline consensus and working groups (e.g., CONSORT-AI, SPIRIT-AI, DECIDE-AI, QUADAS-AI). 

Dr. McCradden is an Associate Scientist with the SickKids Research Institute in the Genetics & Genome Biology Program. She is an Assistant Professor at the Dalla Lana School of Public Health in the Division of Clinical and Public Health.  

Dr. McCradden brings her background in clinical research to her work at SickKids as she explores the intersections of ethics and evidence, and is particularly interested in highlighting the value of a young person’s voice and agency in healthcare. 


Dr. McCradden’s research focuses on novel technologies, including artificial intelligence, machine learning, precision health, and neurotechnologies. These projects involve a unique integration of ethics, computer science, and paediatric healthcare. She is particularly interested in how to responsibly evaluate these new technologies from an evidence perspective, integrating research ethics and evidence-based medicine. Bridging research and practice, Dr. McCradden draws from this work as she leads the development of health policy and research ethics oversight processes to address bias and justice issues in the design, validation, and evaluation of AI technologies.  

Another branch of Dr. McCradden’s research explores the moral attitudes and values of young people concerning the ethical considerations for AI in healthcare. Using qualitative and quantitative methodologies, she conducts interviews, focus groups, and workshops to bring the values of young people into the development of policies and practices governing health AI. 

Her past work has focused on sport ethics, specifically concerning youth athletes and sport violence, and the integration of paediatric bioethics concepts into youth sport. Her graduate thesis explored the neuropsychiatric sequelae of sport-related concussion in youth athletes. 


  • 2017–2020: M.HSc., Bioethics, Joint Centre for Bioethics, University of Toronto, Toronto ON
  • 2010–2017: PhD, Neuroscience, McMaster University, Hamilton ON


  • 2019: Postdoctoral fellow, Ethics of AI in Healthcare, The Hospital for Sick Children - Bioethics and Vector Institute, Toronto ON
  • 2017–2019: Postdoctoral fellow, Neurosurgery, St. Michael’s Hospital/Unity Health, Toronto ON


100 Brilliant Women in AI Ethics List


  1. McCradden M, Stephenson E. Anderson JA. 2020. Clinical research underlies ethical integration of healthcare artificial intelligence. Nature Medicine, 26(9): 1325–1326. 
  2. Sounderajah, V., McCradden, M.D., Liu, X., Rose, S., Ashrafian, H., Collins, G.S., Anderson, J., Bossuyt, P.M., Moher, D. and Darzi, A., 2022. Ethics methods are required as part of reporting guidelines for artificial intelligence in healthcare. Nature Machine Intelligence, 4(4), pp. 316–317.
  3. McCradden MD, Joshi S, Mazwi M, Anderson JAA 2020. Ethical limitations of algorithmic fairness solutions in health care machine learningLancet Digital Health, 2(5): e221–e223.
  4. McCradden, M.D., Anderson, J.A., A. Stephenson, E., Drysdale, E., Erdman, L., Goldenberg, A. and Zlotnik Shaul, R., 2022. A research ethics framework for the clinical translation of healthcare machine learning. The American Journal of Bioethics, 22(5): 8–22.
  5. McCradden, M.D., 2022. Partnering with children and youth to advance artificial intelligence in healthcare. Pediatric Research, pp. 1–3

See a full list of Melissa McCradden's publications

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