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Nuclear Medicine and Artificial Intelligence: Best Practices for Algorithm Development.
Bradshaw, Tyler J; Boellaard, Ronald; Dutta, Joyita; Jha, Abhinav K; Jacobs, Paul; Li, Quanzheng; Liu, Chi; Sitek, Arkadiusz; Saboury, Babak; Scott, Peter J H; Slomka, Piotr J; Sunderland, John J; Wahl, Richard L; Yousefirizi, Fereshteh; Zuehlsdorff, Sven; Rahmim, Arman; Buvat, Irène.
Afiliação
  • Bradshaw TJ; Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin; tbradshaw@wisc.edu.
  • Boellaard R; Department of Radiology and Nuclear Medicine, Cancer Centre Amsterdam, Amsterdam University Medical Centres, Amsterdam, The Netherlands.
  • Dutta J; Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, Massachusetts.
  • Jha AK; Department of Biomedical Engineering and Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri.
  • Jacobs P; MIM Software Inc., Cleveland, Ohio.
  • Li Q; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts.
  • Liu C; Department of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut.
  • Sitek A; Sano Centre for Computational Medicine, Kraków, Poland.
  • Saboury B; Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, Maryland.
  • Scott PJH; Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan.
  • Slomka PJ; Department of Imaging, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, California.
  • Sunderland JJ; Departments of Radiology and Physics, University of Iowa, Iowa City, Iowa.
  • Wahl RL; Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri.
  • Yousefirizi F; Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, British Columbia, Canada.
  • Zuehlsdorff S; Siemens Medical Solutions USA, Inc., Hoffman Estates, Illinois.
  • Rahmim A; Departments of Radiology and Physics, University of British Columbia, Vancouver, British Columbia, Canada; and.
  • Buvat I; Institut Curie, Université PSL, INSERM, Université Paris-Saclay, Orsay, France.
J Nucl Med ; 63(4): 500-510, 2022 04.
Article em En | MEDLINE | ID: mdl-34740952
ABSTRACT
The nuclear medicine field has seen a rapid expansion of academic and commercial interest in developing artificial intelligence (AI) algorithms. Users and developers can avoid some of the pitfalls of AI by recognizing and following best practices in AI algorithm development. In this article, recommendations on technical best practices for developing AI algorithms in nuclear medicine are provided, beginning with general recommendations and then continuing with descriptions of how one might practice these principles for specific topics within nuclear medicine. This report was produced by the AI Task Force of the Society of Nuclear Medicine and Molecular Imaging.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Medicina Nuclear Tipo de estudo: Guideline / Prognostic_studies Idioma: En Revista: J Nucl Med Ano de publicação: 2022 Tipo de documento: Article
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Medicina Nuclear Tipo de estudo: Guideline / Prognostic_studies Idioma: En Revista: J Nucl Med Ano de publicação: 2022 Tipo de documento: Article