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Deep Learning Model for Predicting Intradialytic Hypotension Without Privacy Infringement: A Retrospective Two-Center Study.
Kim, Hyung Woo; Heo, Seok-Jae; Kim, Minseok; Lee, Jakyung; Park, Keun Hyung; Lee, Gongmyung; Baeg, Song In; Kwon, Young Eun; Choi, Hye Min; Oh, Dong-Jin; Nam, Chung-Mo; Kim, Beom Seok.
Affiliation
  • Kim HW; Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea.
  • Heo SJ; Department of Biostatistics and Computing, Yonsei University Graduate School, Seoul, South Korea.
  • Kim M; Department of Biostatistics and Computing, Yonsei University Graduate School, Seoul, South Korea.
  • Lee J; Department of Biostatistics and Computing, Yonsei University Graduate School, Seoul, South Korea.
  • Park KH; Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea.
  • Lee G; Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea.
  • Baeg SI; Department of Internal Medicine, Myongji Hospital, Hanyang University College of Medicine, Goyang, South Korea.
  • Kwon YE; Department of Internal Medicine, Myongji Hospital, Hanyang University College of Medicine, Goyang, South Korea.
  • Choi HM; Department of Internal Medicine, Myongji Hospital, Hanyang University College of Medicine, Goyang, South Korea.
  • Oh DJ; Department of Internal Medicine, Myongji Hospital, Hanyang University College of Medicine, Goyang, South Korea.
  • Nam CM; Department of Biostatistics and Computing, Yonsei University Graduate School, Seoul, South Korea.
  • Kim BS; Division of Biostatistics, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, South Korea.
Front Med (Lausanne) ; 9: 878858, 2022.
Article in En | MEDLINE | ID: mdl-35872786
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Front Med (Lausanne) Year: 2022 Document type: Article Affiliation country: Corea del Sur Country of publication: Suiza
Fulltext
Add to My VHL
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Front Med (Lausanne) Year: 2022 Document type: Article Affiliation country: Corea del Sur Country of publication: Suiza