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Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem
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 trus...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Society of Nuclear Medicine
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9902852/ https://www.ncbi.nlm.nih.gov/pubmed/36522184 http://dx.doi.org/10.2967/jnumed.121.263703 |
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author | Saboury, Babak Bradshaw, Tyler Boellaard, Ronald Buvat, Irène Dutta, Joyita Hatt, Mathieu Jha, Abhinav K. Li, Quanzheng Liu, Chi McMeekin, Helena Morris, Michael A. Scott, Peter J.H. Siegel, Eliot Sunderland, John J. Pandit-Taskar, Neeta Wahl, Richard L. Zuehlsdorff, Sven Rahmim, Arman |
author_facet | Saboury, Babak Bradshaw, Tyler Boellaard, Ronald Buvat, Irène Dutta, Joyita Hatt, Mathieu Jha, Abhinav K. Li, Quanzheng Liu, Chi McMeekin, Helena Morris, Michael A. Scott, Peter J.H. Siegel, Eliot Sunderland, John J. Pandit-Taskar, Neeta Wahl, Richard L. Zuehlsdorff, Sven Rahmim, Arman |
author_sort | Saboury, Babak |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9902852 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Society of Nuclear Medicine |
record_format | MEDLINE/PubMed |
spelling | pubmed-99028522023-04-19 Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem Saboury, Babak Bradshaw, Tyler Boellaard, Ronald Buvat, Irène Dutta, Joyita Hatt, Mathieu Jha, Abhinav K. Li, Quanzheng Liu, Chi McMeekin, Helena Morris, Michael A. Scott, Peter J.H. Siegel, Eliot Sunderland, John J. Pandit-Taskar, Neeta Wahl, Richard L. Zuehlsdorff, Sven Rahmim, Arman J Nucl Med The State of the Art 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. Society of Nuclear Medicine 2023-02 /pmc/articles/PMC9902852/ /pubmed/36522184 http://dx.doi.org/10.2967/jnumed.121.263703 Text en © 2023 by the Society of Nuclear Medicine and Molecular Imaging. https://creativecommons.org/licenses/by/4.0/Immediate Open Access: Creative Commons Attribution 4.0 International License (CC BY) allows users to share and adapt with attribution, excluding materials credited to previous publications. License: https://creativecommons.org/licenses/by/4.0/. Details: http://jnm.snmjournals.org/site/misc/permission.xhtml. |
spellingShingle | The State of the Art Saboury, Babak Bradshaw, Tyler Boellaard, Ronald Buvat, Irène Dutta, Joyita Hatt, Mathieu Jha, Abhinav K. Li, Quanzheng Liu, Chi McMeekin, Helena Morris, Michael A. Scott, Peter J.H. Siegel, Eliot Sunderland, John J. Pandit-Taskar, Neeta Wahl, Richard L. Zuehlsdorff, Sven Rahmim, Arman Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem |
title | Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem |
title_full | Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem |
title_fullStr | Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem |
title_full_unstemmed | Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem |
title_short | Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem |
title_sort | artificial intelligence in nuclear medicine: opportunities, challenges, and responsibilities toward a trustworthy ecosystem |
topic | The State of the Art |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9902852/ https://www.ncbi.nlm.nih.gov/pubmed/36522184 http://dx.doi.org/10.2967/jnumed.121.263703 |
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