Ethical Considerations for Artificial Intelligence in Medical Imaging: Data Collection, Development, and Evaluation
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
Abstract
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 and Molecular Imaging has identified 4 major ethical risks: privacy of data subjects, data quality and model efficacy, fairness toward marginalized 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.