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- Q91848838 description "article scientifique publié en 2020" @default.
- Q91848838 description "artículu científicu espublizáu n'abril de 2020" @default.
- Q91848838 description "im April 2020 veröffentlichter wissenschaftlicher Artikel" @default.
- Q91848838 description "scientific article published on 13 April 2020" @default.
- Q91848838 description "wetenschappelijk artikel" @default.
- Q91848838 description "наукова стаття, опублікована 13 квітня 2020" @default.
- Q91848838 name "A method of using deep learning to predict three-dimensional dose distributions for intensity-modulated radiotherapy of rectal cancer" @default.
- Q91848838 name "A method of using deep learning to predict three-dimensional dose distributions for intensity-modulated radiotherapy of rectal cancer" @default.
- Q91848838 type Item @default.
- Q91848838 label "A method of using deep learning to predict three-dimensional dose distributions for intensity-modulated radiotherapy of rectal cancer" @default.
- Q91848838 label "A method of using deep learning to predict three-dimensional dose distributions for intensity-modulated radiotherapy of rectal cancer" @default.
- Q91848838 prefLabel "A method of using deep learning to predict three-dimensional dose distributions for intensity-modulated radiotherapy of rectal cancer" @default.
- Q91848838 prefLabel "A method of using deep learning to predict three-dimensional dose distributions for intensity-modulated radiotherapy of rectal cancer" @default.
- Q91848838 P1433 Q91848838-385C02C4-8EC9-4BFB-82D2-A041F5778934 @default.
- Q91848838 P1476 Q91848838-EC4E5A56-5876-4249-AF01-08DBD387E656 @default.
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- Q91848838 P2093 Q91848838-4933F222-33A3-4BAD-988C-03EA3B11289C @default.
- Q91848838 P2093 Q91848838-4B4D6C81-1992-426E-AE97-29CA01FCBD3A @default.
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- Q91848838 P31 Q91848838-A3B91203-84BE-4481-8E3F-AAF44F0F1F51 @default.
- Q91848838 P356 Q91848838-1B3AF2C8-C064-4E38-8187-D1B6407B467C @default.
- Q91848838 P4510 Q91848838-ADEF262E-AF32-47A6-B4AD-195155C12D2E @default.
- Q91848838 P577 Q91848838-4E9A7301-FB5D-4E53-AF2F-A08944217547 @default.
- Q91848838 P698 Q91848838-034207E8-D6CC-4BA3-A1DE-D4366C00590D @default.
- Q91848838 P921 Q91848838-B96F498D-D999-412C-AF8D-41B7CDCC4FDB @default.
- Q91848838 P932 Q91848838-3E6DE505-A80A-4CEE-8F9E-E8F2036408C0 @default.
- Q91848838 P356 ACM2.12849 @default.
- Q91848838 P698 32281254 @default.
- Q91848838 P1433 Q27714925 @default.
- Q91848838 P1476 "A method of using deep learning to predict three-dimensional dose distributions for intensity-modulated radiotherapy of rectal cancer" @default.
- Q91848838 P2093 "Jieping Zhou" @default.
- Q91848838 P2093 "Liusi Sheng" @default.
- Q91848838 P2093 "X George Xu" @default.
- Q91848838 P2093 "Xi Pei" @default.
- Q91848838 P2093 "Yankui Chang" @default.
- Q91848838 P2093 "Yuchen Song" @default.
- Q91848838 P2093 "Zhao Peng" @default.
- Q91848838 P2860 Q32032136 @default.
- Q91848838 P31 Q13442814 @default.
- Q91848838 P356 "10.1002/ACM2.12849" @default.
- Q91848838 P4510 Q197536 @default.
- Q91848838 P577 "2020-04-13T00:00:00Z" @default.
- Q91848838 P698 "32281254" @default.
- Q91848838 P921 Q197536 @default.
- Q91848838 P932 "7286006" @default.