Establishing the Ethical Foundations for Artificial Intelligence in Nuclear Medicine

Abstract

1433 Objectives: Artificial intelligence (AI) in Nuclear Medicine is a disruptive technology with the to re-shape clinical and research practice. AI itself is not new to nuclear medicine, medical imaging or medicine generally, however, recent advances in machine learning (ML) and deep learning (DL) have driven broader applications and rapid adoption of new algorithms. With this change comes the challenge of recognizing and addressing ethical issues. With rapid adoption of ML and DL in Nuclear Medicine, recognition of ethical issues is occurring in parallel to innovation and implementation while adoption of contingencies and ethical foundations for proactive management has fallen behind. Ethical considerations relate to three distinct areas: data use, algorithm selection, and deployment strategy in clinical and research practice. Here, the ethical challenges associated with the implementation of AI in Nuclear Medicine are explored and 16 ethical principles are proposed as a framework (figure 1) in which to apply the principles of AI in Nuclear Medicine. Figure 1: Ethical and social considerations for AI in Nuclear Medicine and Molecular Imaging include the 3 aspects of the inner triangle; practice, data and AI. Scaffolded to the ethical and social considerations are the 16 principles proposed as the framework that should guide the use of AI in Nuclear Medicine and Molecular Imaging.

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