Fairness and Ethics in Artificial Intelligence-Based Medical Imaging

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Author(s): Satvik Tripathi (College of Computing & Informatics, Drexel University, USA)and Thomas Heinrich Musiolik (Berlin University of the Arts, Germany)
Copyright: 2022
Pages: 15
Source title: Ethical Implications of Reshaping Healthcare With Emerging Technologies
Source Author(s)/Editor(s): Thomas Heinrich Musiolik (Berlin University of the Arts, Germany)and Alexiei Dingli (University of Malta, Malta)
DOI: 10.4018/978-1-7998-7888-9.ch004

Keywords: Ethics & Law / Medical Information Science Reference / Medical Technologies / Security & Forensics

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Abstract

Artificial intelligence has a huge array of current and potential applications in healthcare and medicine. Ethical issues arising due to algorithmic biases are one of the greatest challenges faced in the generalizability of AI models today. The authors address 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, they 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. These AI-based medical imaging models will then be completely implemented in healthcare facilities and institutions all around the world, even in the remotest areas, making diagnosis and patient care both cheaper and freely accessible.

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Fairness and Ethics in Artificial Intelligence-Based Medical Imaging

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