TY - JOUR
T1 - Ethical considerations for artificial intelligence in medical imaging
T2 - Data collection, development, and evaluation
AU - Herington, Jonathan
AU - McCradden, Melissa D.
AU - Creel, Kathleen
AU - Boellaard, Ronald
AU - Jones, Elizabeth C.
AU - Jha, Abhinav K.
AU - Rahmim, Arman
AU - Scott, Peter J. H.
AU - Sunderland, John J.
AU - Wahl, Richard L.
AU - Zuehlsdorff, Sven
AU - Saboury, Babak
N1 - Funding Information: Melissa McCradden acknowledges funding from the SickKids Foundation pertaining to her role as the John and Melinda Thompson Director of AI in Medicine at the Hospital for Sick Children. Abhinav Jha acknowledges support from NIH R01EB031051-02S1. Sven Zuehlsdorff is a full-time employee of Siemens Medical Solutions USA, Inc. No other potential conflict of interest relevant to this article was reported. Publisher Copyright: © 2023 Society of Nuclear Medicine Inc.. All rights reserved.
PY - 2023
Y1 - 2023
N2 - The development of artificial intelligence (AI) within nuclear imaging involves several ethically fraught components at different stages of the machine learning pipeline, including during data collection, model training and validation, and clinical use. Drawing on the traditional principles of medical and research ethics, and highlighting the need to ensure health justice, the AI task force of the Society of Nuclear Medicine andMolecular Imaging has identified 4major ethical risks: privacy of data subjects, data quality andmodel efficacy, fairness towardmarginalized populations, and transparency of clinical performance. We provide preliminary recommendations to developers of AI-driven medical devices for mitigating the impact of these risks on patients and populations.
AB - The development of artificial intelligence (AI) within nuclear imaging involves several ethically fraught components at different stages of the machine learning pipeline, including during data collection, model training and validation, and clinical use. Drawing on the traditional principles of medical and research ethics, and highlighting the need to ensure health justice, the AI task force of the Society of Nuclear Medicine andMolecular Imaging has identified 4major ethical risks: privacy of data subjects, data quality andmodel efficacy, fairness towardmarginalized populations, and transparency of clinical performance. We provide preliminary recommendations to developers of AI-driven medical devices for mitigating the impact of these risks on patients and populations.
KW - AI as medical device
KW - AI ethics
KW - Health disparity
KW - Socioeconomic determinants of health
KW - Software as medical device
UR - http://www.scopus.com/inward/record.url?scp=85178649009&partnerID=8YFLogxK
U2 - https://doi.org/10.2967/jnumed.123.266080
DO - https://doi.org/10.2967/jnumed.123.266080
M3 - Article
C2 - 37827839
SN - 0161-5505
VL - 64
SP - 1848
EP - 1854
JO - Journal of nuclear medicine
JF - Journal of nuclear medicine
IS - 12
ER -