Canadian Association of Radiologists White Paper on Ethical and Legal Issues Related to Artificial Intelligence in Radiology

Author:

,Jaremko Jacob L.1,Azar Marleine2,Bromwich Rebecca3,Lum Andrea4,Alicia Cheong Li Hsia5,Gibert Martin6,Laviolette François7,Gray Bruce8,Reinhold Caroline9,Cicero Mark10,Chong Jaron9,Shaw James11,Rybicki Frank J.1213,Hurrell Casey14,Lee Emil141516,Tang An17

Affiliation:

1. Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Alberta, Canada

2. Department of Medicine, Université de Montréal, Montréal, Quebec, Canada

3. Department of Law and Legal Studies, Carleton University, Ottawa, Canada

4. Department of Medical Imaging, Western University, London, Ontario, Canada

5. Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada

6. Centre de recherche en éthique, Université de Montréal, Montréal, Quebec, Canada

7. Department of Computer Science, Université Laval, Québec, Quebec, Canada

8. Department of Medical Imaging, St Michael's Hospital, University of Toronto, Toronto, Ontario, Canada

9. Department of Radiology, McGill University Health Center, Montreal, Quebec, Canada

10. 16 Bit Inc, Toronto, Ontario, Canada

11. Institute for Health System Solutions and Virtual Care, Women's College Hospital, Toronto, Ontario, Canada

12. Department of Radiology, The University of Ottawa Faculty of Medicine and The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada

13. Imagia Cybernetics, Montreal, Quebec, Canada

14. Canadian Association of Radiologists, Ottawa, Ontario, Canada

15. Department of Radiology, Valley Medical Imaging, Langley, British Columbia, Canada

16. Department of Medical Imaging, Fraser Health Authority, British Columbia, Canada

17. Department of Radiology, Radio-oncology, and Nuclear Medicine, Université de Montréal, Montréal, Quebec, Canada

Abstract

Artificial intelligence (AI) software that analyzes medical images is becoming increasingly prevalent. Unlike earlier generations of AI software, which relied on expert knowledge to identify imaging features, machine learning approaches automatically learn to recognize these features. However, the promise of accurate personalized medicine can only be fulfilled with access to large quantities of medical data from patients. This data could be used for purposes such as predicting disease, diagnosis, treatment optimization, and prognostication. Radiology is positioned to lead development and implementation of AI algorithms and to manage the associated ethical and legal challenges. This white paper from the Canadian Association of Radiologists provides a framework for study of the legal and ethical issues related to AI in medical imaging, related to patient data (privacy, confidentiality, ownership, and sharing); algorithms (levels of autonomy, liability, and jurisprudence); practice (best practices and current legal framework); and finally, opportunities in AI from the perspective of a universal health care system.

Funder

Medical Imaging Consultants

Alberta Health Services

Ontario Health Technologies Fund

VHA Home Health Care

Canadian Institutes of Health Research

IBM Watson

Publisher

SAGE Publications

Subject

Radiology Nuclear Medicine and imaging,General Medicine

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