PT  - JOURNAL ARTICLE
AU  - Saboury, Babak
AU  - Bradshaw, Tyler
AU  - Boellaard, Ronald
AU  - Buvat, Irène
AU  - Dutta, Joyita
AU  - Hatt, Mathieu
AU  - Jha, Abhinav K.
AU  - Li, Quanzheng
AU  - Liu, Chi
AU  - McMeekin, Helena
AU  - Morris, Michael A.
AU  - Pandit-Taskar, Neeta
AU  - Scott, Peter J.H.
AU  - Siegel, Eliot
AU  - Sunderland, John J.
AU  - Pandit-Taskar, Neeta
AU  - Wahl, Richard L.
AU  - Zuehlsdorff, Sven
AU  - Rahmim, Arman
TI  - Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem
AID  - 10.2967/jnumed.121.263703
DP  - 2022 Dec 01
TA  - Journal of Nuclear Medicine
PG  - jnumed.121.263703
4099  - http://jnm.snmjournals.org/content/early/2022/12/15/jnumed.121.263703.short
4100  - http://jnm.snmjournals.org/content/early/2022/12/15/jnumed.121.263703.full
AB  - Trustworthiness is a core tenet of medicine. The patient-physician relationship is evolving from a dyad to a broader ecosystem of healthcare. With the emergence of artificial intelligence (AI) in medicine, the elements of trust must be revisited. We envision a roadmap for the establishment of trustworthy AI ecosystems in nuclear medicine. In this report, AI is contextualized in the history of technological 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 requires a concerted effort to promote the rational and safe deployment of this innovative technology by engaging patients, nuclear medicine physicians, scientists, technologists, referring providers, among other stakeholders, while protecting our patients and society. This strategic plan is prepared by the AI Task Force of the Society of Nuclear Medicine and Molecular Imaging (SNMMI).