Inserm, U1030 Molecular Radiotherapy and Therapeutic Innovation, Université Paris-Saclay, Gustave-Roussy, Villejuif, France; Department of Radiation Oncology, Gustave-Roussy, Villejuif, France.
Department of Radiotherapy, Institut de Cancérologie Strasbourg Europe (ICANS), Strasbourg, France; Icube, CNRS UMR 7357, team Images, Strasbourg, France.
Cancer Radiother. 2024 Nov;28(6-7):503-509. doi: 10.1016/j.canrad.2024.09.003. Epub 2024 Oct 15.
The integration of artificial intelligence, particularly deep learning algorithms, into radiotherapy represents a transformative shift in the field, enhancing accuracy, efficiency, and personalized care. This paper explores the multifaceted impact of artificial intelligence on radiotherapy, the evolution of the roles of radiation oncologists and medical physicists, and the associated practical challenges. The adoption of artificial intelligence promises to revolutionize the profession by automating repetitive tasks, improving diagnostic precision, and enabling adaptive radiotherapy. However, it also introduces significant risks, such as automation bias, verification failures, and the potential erosion of clinical skills. Ethical considerations, such as maintaining patient autonomy and addressing biases in artificial intelligence systems, are critical to ensuring the responsible use of artificial intelligence. Continuous training and development of robust quality assurance programs are required to mitigate these risks and maximize the benefits of artificial intelligence in radiotherapy.
人工智能，尤其是深度学习算法，在放射治疗中的应用代表了该领域的重大变革，提高了准确性、效率和个性化护理。本文探讨了人工智能对放射治疗的多方面影响，以及放射肿瘤学家和医学物理学家角色的演变，以及相关的实际挑战。人工智能的采用有望通过自动化重复任务、提高诊断精度和实现自适应放射治疗来彻底改变这一职业。然而，它也带来了重大风险，如自动化偏差、验证失败以及临床技能的潜在侵蚀。人工智能系统中的伦理考虑，如维护患者自主权和解决偏见问题，对于确保人工智能的负责任使用至关重要。需要持续培训和开发强大的质量保证计划，以减轻这些风险并最大限度地发挥人工智能在放射治疗中的益处。
