Selected article for: "artificial intelligence and medical science"

Author: Kang, John; Thompson, Reid; Aneja, Sanjay; Lehman, Constance; Trister, Andrew; Zou, James; Obcemea, Ceferino; Naqa, Issam El
Title: NCI Workshop on Artificial Intelligence in Radiation Oncology: Training the Next Generation
  • Cord-id: hyyd9ezw
  • Document date: 2019_10_18
  • ID: hyyd9ezw
    Snippet: Artificial intelligence (AI) is about to touch every aspect of radiotherapy from consultation, treatment planning, quality assurance, therapy delivery, to outcomes reporting. There is an urgent need to train radiation oncologists and medical physicists in data science to help shepherd artificial intelligence 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 expan
    Document: Artificial intelligence (AI) is about to touch every aspect of radiotherapy from consultation, treatment planning, quality assurance, therapy delivery, to outcomes reporting. There is an urgent need to train radiation oncologists and medical physicists in data science to help shepherd artificial intelligence 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. In this perspective article by the Training and Education Working Group from the National Cancer Institute (NCI) Workshop on AI in Radiation Oncology (Shady Grove, MD, April 4-5, 2019), we provide and discuss Action Points relevant for future trainees interested in radiation oncology artificial intelligence: (1) creating AI awareness and proper conduct; (2) developing a dedicated didactic curriculum; (3) creating a publicly available database of training resources; and (4) accelerating the translation process of AI into clinical practice.

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