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Ethical Framework for Responsible Foundational Models in Medical Imaging (2406.11868v1)

Published 14 Apr 2024 in cs.CY and cs.AI

Abstract: Foundational models (FMs) have tremendous potential to revolutionize medical imaging. However, their deployment in real-world clinical settings demands extensive ethical considerations. This paper aims to highlight the ethical concerns related to FMs and propose a framework to guide their responsible development and implementation within medicine. We meticulously examine ethical issues such as privacy of patient data, bias mitigation, algorithmic transparency, explainability and accountability. The proposed framework is designed to prioritize patient welfare, mitigate potential risks, and foster trust in AI-assisted healthcare.

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Authors (9)
  1. Abhijit Das (25 papers)
  2. Debesh Jha (78 papers)
  3. Jasmer Sanjotra (1 paper)
  4. Onkar Susladkar (12 papers)
  5. Suramyaa Sarkar (1 paper)
  6. Ashish Rauniyar (6 papers)
  7. Nikhil Tomar (1 paper)
  8. Vanshali Sharma (9 papers)
  9. Ulas Bagci (154 papers)
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