Informed consent in radiation oncology: Adapting to the age of artificial intelligence

The integration of artificial intelligence (AI) into radiation oncology is significantly enhancing treatment precision and efficiency. However, this technological advancement presents substantial ethical challenges, particularly in the context of informed consent. Traditional consent taking, which relies on physician discretion, must evolve to address the complexities introduced by AI systems. Key ethical considerations include ensuring that patients understand the role of AI in their treatment, transparency in AI-driven decision-making processes, and the protection of patient privacy. A refined approach to informed consent is necessary to navigate these challenges. This approach should prioritize clear communication, emphasize the complementary role of AI in treatment and the decision-making process, and address potential biases inherent in AI algorithms.

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Publication Details

Journal
Advances in Radiotherapy & Nuclear Medicine
Published
2025-08-18
DOI
https://doi.org/10.36922/arnm025250030
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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Informed consent in radiation oncology: Adapting to the age of artificial intelligence

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Informed consent in radiation oncology: Adapting to the age of artificial intelligence

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article en

Abstract

The integration of artificial intelligence (AI) into radiation oncology is significantly enhancing treatment precision and efficiency. However, this technological advancement presents substantial ethical challenges, particularly in the context of informed consent. Traditional consent taking, which relies on physician discretion, must evolve to address the complexities introduced by AI systems. Key ethical considerations include ensuring that patients understand the role of AI in their treatment, transparency in AI-driven decision-making processes, and the protection of patient privacy. A refined approach to informed consent is necessary to navigate these challenges. This approach should prioritize clear communication, emphasize the complementary role of AI in treatment and the decision-making process, and address potential biases inherent in AI algorithms.

Advances in Radiotherapy & Nuclear MedicineVol. 3(3)
Openalex Percentile: Top 85%
Artificial Intelligence in Healthcare and Education
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