Regarding article 5, "Fairness and Ethics in Artificial Intelligence-Based Medical Imaging":
"Given the vast number of issues concerning usage, failure, success, strategies, and applications of medical imaging, the Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention encompasses the most pertinent research on the applications, impacts, uses, and strategies of medical imaging. This chapter addresses safety and regulatory barriers that impede data sharing in medicine as well as potential changes to existing techniques and frameworks that might allow ethical data sharing for machine learning. With these developments in view, the authors also present different algorithmic models that are being used to develop machine learning-based medical systems that will potentially evolve to be free of the sample, annotator, and temporal bias.“
– Prof. Thomas Heinrich Musiolik, Berlin University of the Arts, Germany