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
Lien Pubmed
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