PT  - JOURNAL ARTICLE
AU  - Babak Saboury
AU  - Tyler Bradshaw
AU  - Ronald Boellaard
AU  - Irène Buvat
AU  - Joyita Dutta
AU  - Mathieu Hatt
AU  - Abhinav K. Jha
AU  - Quanzheng Li
AU  - Chi Liu
AU  - Helena McMeekin
AU  - Michael A. Morris
AU  - Peter J.H. Scott
AU  - Eliot Siegel
AU  - John J. Sunderland
AU  - Neeta Pandit-Taskar
AU  - Richard L. Wahl
AU  - Sven Zuehlsdorff
AU  - Arman Rahmim
TI  - Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem
AID  - 10.2967/jnumed.121.263703
DP  - 2023 Feb 01
TA  - Journal of Nuclear Medicine
PG  - 188--196
VI  - 64
IP  - 2
4099  - http://jnm.snmjournals.org/content/64/2/188.short
4100  - http://jnm.snmjournals.org/content/64/2/188.full
SO  - J Nucl Med2023 Feb 01; 64
AB  - Trustworthiness is a core tenet of medicine. The patient–physician relationship is evolving from a dyad to a broader ecosystem of health care. With the emergence of artificial intelligence (AI) in medicine, the elements of trust must be revisited. We envision a road map for the establishment of trustworthy AI ecosystems in nuclear medicine. In this report, AI is contextualized in the history of technologic revolutions. Opportunities for AI applications in nuclear medicine related to diagnosis, therapy, and workflow efficiency, as well as emerging challenges and critical responsibilities, are discussed. Establishing and maintaining leadership in AI require a concerted effort to promote the rational and safe deployment of this innovative technology by engaging patients, nuclear medicine physicians, scientists, technologists, and referring providers, among other stakeholders, while protecting our patients and society. This strategic plan was prepared by the AI task force of the Society of Nuclear Medicine and Molecular Imaging.