Ethical Considerations for Artificial Intelligence in Medical Imaging: Data Collection, Development, and Evaluation

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.

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“…Ethical concerns of AI in medical application mainly revolve around general issues of AI application and unique issues related to medical treatment, of which the most universal is data privacy. Medical data from medical imaging usually contains patient identity information, health status, disease diagnosis and treatment, involving patient privacy and possessing exceptional sensitivity and important value [ 85 ]. In the context of big data, besides taking technical measures such as "anonymization" and encrypted storage, strengthening data management is the top priority to strike a balance between medical data sharing and privacy security.…”