Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem

¹ Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, United States;
² Department of Radiology, University of Wisconsin - Madison, United States;
³ Dept of Radiology & Nuclear Medicine, Cancer Centre Amsterdam, Amsterdam University Medical Centres;
⁴ Institut Curie, Université PSL, Inserm, Université Paris-Saclay, France;
⁵ Department of Electrical and Computer Engineering, University of Massachusetts Lowell;
⁶ LaTIM, INSERM, UMR 1101, University of Brest, France;
⁷ Mallinckrodt Institute of Radiology, Washington University in St. Louis, United States;
⁸ Department of Radiology, Massachusetts General Hospital and Harvard Medical School, United States;
⁹ Department of Radiology and Biomedical Imaging, Yale University, United States;
¹⁰ Department of Clinical Physics, Barts Health NHS Trust, United Kingdom;
¹¹ Department of Radiology, Memorial Sloan Kettering Cancer, United States;
¹² Department of Radiology, University of Michigan Medical School;
¹³ Department of Radiology and Nuclear Medicine, University of Maryland Medical Center;
¹⁴ Departments of Radiology and Physics, University of Iowa, United States;
¹⁵ Siemens Medical Solutions USA, Inc., United States;
¹⁶ Departments of Radiology and Physics, University of British Columbia, Canada

For correspondence or reprints contact: Babak Saboury, National Institutes of Health(NIH)-Clinical Center, 9000 Rockville Pike, Building 10, Room 1C455, Bethesda, MD 20892, United States. E-mail: babak.saboury@nih.gov

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