Fiche publication


Date publication

novembre 2024

Journal

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique

Auteurs

Membres identifiés du Cancéropôle Est :
Dr MEYER Philippe


Tous les auteurs :
Robert C, Meyer P, Séroussi B, Leroy T, Bibault JE

Résumé

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.

Mots clés

Artificial intelligence, Intelligence artificielle, Radiation oncology, Radiothérapie, Risks, Risques

Référence

Cancer Radiother. 2024 11;28(6-7):503-509