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本文引用的文献

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Mastering the game of Go without human knowledge.无需人类知识即可掌握围棋游戏。
Nature. 2017 Oct 18;550(7676):354-359. doi: 10.1038/nature24270.
2
Machine learning will transform radiology significantly within the next 5 years.机器学习将在未来5年内极大地改变放射学。
Med Phys. 2017 Jun;44(6):2041-2044. doi: 10.1002/mp.12204. Epub 2017 Apr 20.
3
Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks.使用卷积神经网络对头颈部CT图像中的危险器官进行分割。
Med Phys. 2017 Feb;44(2):547-557. doi: 10.1002/mp.12045.
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Mastering the game of Go with deep neural networks and tree search.用深度神经网络和树搜索掌握围棋游戏。
Nature. 2016 Jan 28;529(7587):484-9. doi: 10.1038/nature16961.
5
Pigeons (Columba livia) as Trainable Observers of Pathology and Radiology Breast Cancer Images.鸽子（家鸽）作为乳腺癌病理和放射影像的可训练观察者。
PLoS One. 2015 Nov 18;10(11):e0141357. doi: 10.1371/journal.pone.0141357. eCollection 2015.
6
Medical physics in radiotherapy: The importance of preserving clinical responsibilities and expanding the profession's role in research, education, and quality control.放射治疗中的医学物理：保留临床职责以及扩大该专业在研究、教育和质量控制方面作用的重要性。
Rep Pract Oncol Radiother. 2015 May-Jun;20(3):161-9. doi: 10.1016/j.rpor.2015.01.001. Epub 2015 Feb 19.

Artificial intelligence will soon change the landscape of medical physics research and practice.

作者信息

Xing Lei, Krupinski Elizabeth A, Cai Jing

机构信息

Department of Radiation Oncology, Stanford University, Stanford, CA, 94305, USA.

Department of Radiology & Imaging Sciences, Emory University, Atlanta, GA, 30322, USA.

出版信息

Med Phys. 2018 May;45(5):1791-1793. doi: 10.1002/mp.12831. Epub 2018 Mar 13.

DOI:10.1002/mp.12831
PMID:29476545
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9560775/
Abstract
摘要