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Canadian Association of Radiologists White Paper on Ethical and Legal Issues Related to Artificial Intelligence in Radiology.
Jaremko, Jacob L; Azar, Marleine; Bromwich, Rebecca; Lum, Andrea; Alicia Cheong, Li Hsia; Gibert, Martin; Laviolette, François; Gray, Bruce; Reinhold, Caroline; Cicero, Mark; Chong, Jaron; Shaw, James; Rybicki, Frank J; Hurrell, Casey; Lee, Emil; Tang, An.
Afiliação
  • Jaremko JL; Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Alberta, Canada.
  • Azar M; Department of Medicine, Université de Montréal, Montréal, Quebec, Canada.
  • Bromwich R; Department of Law and Legal Studies, Carleton University, Ottawa, Canada.
  • Lum A; Department of Medical Imaging, Western University, London, Ontario, Canada.
  • Alicia Cheong LH; Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada.
  • Gibert M; Centre de recherche en éthique, Université de Montréal, Montréal, Quebec, Canada.
  • Laviolette F; Department of Computer Science, Université Laval, Québec, Quebec, Canada.
  • Gray B; Department of Medical Imaging, St Michael's Hospital, University of Toronto, Toronto, Ontario, Canada.
  • Reinhold C; Department of Radiology, McGill University Health Center, Montreal, Quebec, Canada.
  • Cicero M; 16 Bit Inc, Toronto, Ontario, Canada.
  • Chong J; Department of Radiology, McGill University Health Center, Montreal, Quebec, Canada.
  • Shaw J; Institute for Health System Solutions and Virtual Care, Women's College Hospital, Toronto, Ontario, Canada.
  • Rybicki FJ; Department of Radiology, The University of Ottawa Faculty of Medicine and The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada; Imagia Cybernetics, Montreal, Quebec, Canada.
  • Hurrell C; Canadian Association of Radiologists, Ottawa, Ontario, Canada.
  • Lee E; Canadian Association of Radiologists, Ottawa, Ontario, Canada; Department of Radiology, Valley Medical Imaging, Langley, British Columbia, Canada; Department of Medical Imaging, Fraser Health Authority, British Columbia, Canada.
  • Tang A; Department of Radiology, Radio-oncology, and Nuclear Medicine, Université de Montréal, Montréal, Quebec, Canada. Electronic address: an.tang@umontreal.ca.
Can Assoc Radiol J ; 70(2): 107-118, 2019 May.
Article em En | MEDLINE | ID: mdl-30962048
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Radiologia / Inteligência Artificial Tipo de estudo: Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans País como assunto: America do norte Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Radiologia / Inteligência Artificial Tipo de estudo: Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans País como assunto: America do norte Idioma: En Ano de publicação: 2019 Tipo de documento: Article