National Cancer Institute Workshop on Artificial Intelligence in Radiation Oncology: Training the Next Generation.
Journal
Practical radiation oncology
ISSN: 1879-8519
Titre abrégé: Pract Radiat Oncol
Pays: United States
ID NLM: 101558279
Informations de publication
Date de publication:
Historique:
received:
30
01
2020
revised:
26
04
2020
accepted:
01
06
2020
pubmed:
17
6
2020
medline:
20
8
2021
entrez:
17
6
2020
Statut:
ppublish
Résumé
Artificial intelligence (AI) is about to touch every aspect of radiation therapy, from consultation to treatment planning, quality assurance, therapy delivery, and outcomes modeling. There is an urgent need to train radiation oncologists and medical physicists in data science to help shepherd AI solutions into clinical practice. Poorly trained personnel may do more harm than good when attempting to apply rapidly developing and complex technologies. As the amount of AI research expands in our field, the radiation oncology community needs to discuss how to educate future generations in this area. The National Cancer Institute (NCI) Workshop on AI in Radiation Oncology (Shady Grove, MD, April 4-5, 2019) was the first of 2 data science workshops in radiation oncology hosted by the NCI in 2019. During this workshop, the Training and Education Working Group was formed by volunteers among the invited attendees. Its members represent radiation oncology, medical physics, radiology, computer science, industry, and the NCI. In this perspective article written by members of the Training and Education Working Group, we provide and discuss action points relevant for future trainees interested in radiation oncology AI: (1) creating AI awareness and responsible conduct; (2) implementing a practical didactic curriculum; (3) creating a publicly available database of training resources; and (4) accelerating learning and funding opportunities. Together, these action points can facilitate the translation of AI into clinical practice.
Identifiants
pubmed: 32544635
pii: S1879-8500(20)30155-7
doi: 10.1016/j.prro.2020.06.001
pmc: PMC7293478
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
74-83Subventions
Organisme : CSRD VA
ID : IK2 CX002049
Pays : United States
Informations de copyright
Copyright © 2020 American Society for Radiation Oncology. All rights reserved.
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