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Artificial intelligence and radiotherapy: Evolution or revolution?

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Artificial intelligence (AI) integration in radiotherapy enhances precision and personalization but poses risks like automation bias. Continuous training and quality assurance are vital for safe AI adoption in radiation oncology.

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Artificial Intelligence in Medicine

Background:

  • Artificial intelligence (AI), especially deep learning, is transforming radiotherapy.
  • AI integration promises enhanced accuracy, efficiency, and personalized patient care.
  • The evolving roles of radiation oncologists and medical physicists are central to this transformation.

Purpose of the Study:

  • To explore the multifaceted impact of AI on radiotherapy.
  • To examine the evolving roles of healthcare professionals in AI-assisted radiotherapy.
  • To identify and address practical challenges and ethical considerations associated with AI in radiotherapy.

Main Methods:

  • Review of current literature and case studies on AI applications in radiotherapy.
  • Analysis of potential benefits, including task automation and improved diagnostic precision.
  • Identification of risks such as automation bias, verification failures, and skill erosion.

Main Results:

  • AI adoption revolutionizes radiotherapy by automating tasks and enabling adaptive treatments.
  • Significant risks include automation bias, verification failures, and potential clinical skill degradation.
  • Ethical considerations, including patient autonomy and AI bias, are critical for responsible implementation.

Conclusions:

  • AI offers substantial benefits for radiotherapy, improving accuracy and personalization.
  • Mitigating risks requires continuous professional training and robust quality assurance programs.
  • Responsible AI integration is essential to maximize benefits while ensuring patient safety and ethical practice.