Ethical Considerations for Artificial Intelligence in Medical Imaging:Deployment and Governance

Jonathan Herington; Melissa D McCradden; Kathleen Creel; Ronald Boellaard; Elizabeth C Jones; Abhinav K Jha; Arman Rahmim; Peter J. H Scott; John J Sunderland; Richard L Wahl; Sven Zuehlsdorff; Babak Saboury

doi:10.2967/jnumed.123.266110

Back

Ethical Considerations for Artificial Intelligence in Medical Imaging:Deployment and Governance

Journal article

Open access

Peer reviewed

Ethical Considerations for Artificial Intelligence in Medical Imaging:Deployment and Governance

Jonathan Herington, Melissa D McCradden, Kathleen Creel, Ronald Boellaard, Elizabeth C Jones, Abhinav K Jha, Arman Rahmim, Peter J. H Scott, John J Sunderland, Richard L Wahl, …

The Journal of nuclear medicine : JNM, Vol.64(10), pp.1509-1515

10/01/2023

DOI: 10.2967/jnumed.123.266110

PMCID: PMC12782051

PMID: 37620051

Files and links (1)

url

https://doi.org/10.2967/jnumed.123.266110View

Published (Version of record) Open Access

Abstract

The deployment of artificial intelligence (AI) has the potential to make nuclear medicine and medical imaging faster, cheaper, and both more effective and more accessible. This is possible, however, only if clinicians and patients feel that these AI medical devices (AIMDs) are trustworthy. Highlighting the need to ensure health justice by fairly distributing benefits and burdens while respecting individual patients’ rights, the AI Task Force of the Society of Nuclear Medicine and Molecular Imaging has identified 4 major ethical risks that arise during the deployment of AIMD: autonomy of patients and clinicians, transparency of clinical performance and limitations, fairness toward marginalized populations, and accountability of physicians and developers. We provide preliminary recommendations for governing these ethical risks to realize the promise of AIMD for patients and populations.

AI ethics

software as medical device

fairness

explain ability

justice

Details

Title: Subtitle: Ethical Considerations for Artificial Intelligence in Medical Imaging:Deployment and Governance
Creators: Jonathan Herington - University of Rochester
Melissa D McCradden - University of Toronto
Kathleen Creel - Northeastern University
Ronald Boellaard
Elizabeth C Jones - National Institutes of Health Clinical Center
Abhinav K Jha - Washington University in St. Louis
Arman Rahmim - University of British Columbia
Peter J. H Scott - University of Michigan
John J Sunderland - University of Iowa
Richard L Wahl - Washington University in St. Louis
Sven Zuehlsdorff
Babak Saboury - National Institutes of Health Clinical Center
Resource Type: Journal article
Publication Details: The Journal of nuclear medicine : JNM, Vol.64(10), pp.1509-1515
DOI: 10.2967/jnumed.123.266110
PMID: 37620051
PMCID: PMC12782051
NLM abbreviation: J Nucl Med
ISSN: 0161-5505
eISSN: 1535-5667
Publisher: SOC NUCLEAR MEDICINE INC
Grant note: National Institute of Biomedical Imaging and Bioengineering: R01EB021155
Language: English
Date published: 10/01/2023
Academic Unit: Radiology; Physics and Astronomy; Radiation Oncology
Record Identifier: 9984793978102771

Metrics

5 Record Views

25 Times Cited - Web of Science