  Artificial intelligence (AI) is about to touch every aspect of radiotherapy
from consultation, treatment planning, quality assurance, therapy delivery, to
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
(https://dctd.cancer.gov/NewsEvents/20190523_ai_in_radiation_oncology.htm) of
two 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)
accelerate learning and funding opportunities. Together, these Action Points
can facilitate the translation of AI into clinical practice.
