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Ethical, Regulatory, and Practical Challenges in Artificial Intelligence-Driven Chest Imaging.

Juliana Barreto Caldas de Lima1, Ian Griffin2, Jessica Shapiro Gemmell2

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Artificial intelligence (AI) improves chest imaging by enhancing accuracy and workflows. Addressing challenges like bias, privacy, and regulation is key for responsible AI adoption in radiology for better patient outcomes.

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Area of Science:

  • Radiology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Artificial intelligence (AI) offers significant potential to improve chest imaging.
  • AI can enhance diagnostic accuracy, streamline radiologist workflows, and personalize patient care.

Purpose of the Study:

  • To examine the barriers hindering AI adoption in chest imaging.
  • To discuss ethical, regulatory, and practical challenges associated with AI implementation.
  • To propose strategies for responsible AI integration in radiology.

Main Methods:

  • Review of current literature and expert perspectives on AI in chest imaging.
  • Analysis of challenges including bias, transparency, accountability, and data privacy.
  • Exploration of regulatory pathways and practical integration considerations.

Main Results:

  • Key barriers include ethical concerns (bias, fairness), regulatory hurdles (approval, adaptability), and practical issues (workflow integration, generalizability, cost).
  • Addressing these requires interdisciplinary collaboration, robust validation, and continuous education for radiologists.

Conclusions:

  • Responsible AI adoption in chest imaging is crucial for leveraging its full potential.
  • Overcoming identified challenges will lead to enhanced patient outcomes and improved diagnostic processes.
  • Continuous learning and adaptation are essential for the successful integration of AI tools in clinical practice.