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Image-based deep learning model for predicting pathological response in rectal cancer using post-chemoradiotherapy magnetic resonance imaging.
Jang, Bum-Sup; Lim, Yu Jin; Song, Changhoon; Jeon, Seung Hyuck; Lee, Keun-Wook; Kang, Sung-Bum; Lee, Yoon Jin; Kim, Jae-Sung.
Affiliation
  • Jang BS; Department of Radiation Oncology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
  • Lim YJ; Department of Radiation Oncology, Kyung Hee University Medical Center, Kyung Hee University School of Medicine, Seoul, Republic of Korea.
  • Song C; Department of Radiation Oncology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
  • Jeon SH; Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.
  • Lee KW; Department of Internal Medicine, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
  • Kang SB; Department of Surgery, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
  • Lee YJ; Department of Radiology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea. Electronic address: yoonjin319@gmail.com.
  • Kim JS; Department of Radiation Oncology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea. Electronic address: jskim@snubh.org.
Radiother Oncol ; 161: 183-190, 2021 08.
Article in En | MEDLINE | ID: mdl-34139211
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Rectal Neoplasms / Deep Learning Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Radiother Oncol Year: 2021 Document type: Article Country of publication: Ireland
Fulltext
Add to My VHL
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PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Rectal Neoplasms / Deep Learning Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Radiother Oncol Year: 2021 Document type: Article Country of publication: Ireland