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Nuclear Medicine and Artificial Intelligence: Best Practices for Algorithm Development
88
Zitationen
17
Autoren
2021
Jahr
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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Autoren
Institutionen
- University of Wisconsin System(US)
- University of Wisconsin–Madison(US)
- University of Massachusetts Lowell(US)
- Washington University in St. Louis(US)
- Mallinckrodt (United States)(US)
- Massachusetts General Hospital(US)
- Harvard University(US)
- Yale University(US)
- National Institutes of Health Clinical Center(US)
- University of Michigan(US)
- Cedars-Sinai Medical Center(US)
- University of Iowa(US)
- University of British Columbia(CA)
- Inserm(FR)
- Institut Curie(FR)
- Université Paris Sciences et Lettres(FR)
- Université Paris-Saclay(FR)