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Cancer Drug Response Profile scan (CDRscan): A Deep Learning Model That Predicts Drug Effectiveness from Cancer Genomic Signature.
Chang, Yoosup; Park, Hyejin; Yang, Hyun-Jin; Lee, Seungju; Lee, Kwee-Yum; Kim, Tae Soon; Jung, Jongsun; Shin, Jae-Min.
Afiliación
  • Chang Y; Yongin in silico Medical Research Centre, Syntekabio Inc., 283 Dongbaekjungang-ro, C508, Giheung-gu, Yongin, Gyeonggi-do, 17006, South Korea.
  • Park H; Yongin in silico Medical Research Centre, Syntekabio Inc., 283 Dongbaekjungang-ro, C508, Giheung-gu, Yongin, Gyeonggi-do, 17006, South Korea.
  • Yang HJ; Gwanghwamun Medical Study Centre, Syntekabio Inc., 92 Saemunan-ro, #1708, Jongno-gu, Seoul, 03186, South Korea.
  • Lee S; Yongin in silico Medical Research Centre, Syntekabio Inc., 283 Dongbaekjungang-ro, C508, Giheung-gu, Yongin, Gyeonggi-do, 17006, South Korea.
  • Lee KY; Gwanghwamun Medical Study Centre, Syntekabio Inc., 92 Saemunan-ro, #1708, Jongno-gu, Seoul, 03186, South Korea.
  • Kim TS; Faculty of Medicine, University of Queensland, Brisbane, QLD, 4072, Australia.
  • Jung J; Gwanghwamun Medical Study Centre, Syntekabio Inc., 92 Saemunan-ro, #1708, Jongno-gu, Seoul, 03186, South Korea.
  • Shin JM; Department of Clinical Medical Sciences, Seoul National University College of Medicine, 71 Ihwajang-gil, Jongno-gu, 03087, Seoul, South Korea.
Sci Rep ; 8(1): 8857, 2018 06 11.
Article en En | MEDLINE | ID: mdl-29891981
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Medicina de Precisión / Aprendizaje Profundo / Neoplasias / Antineoplásicos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2018 Tipo del documento: Article País de afiliación: Corea del Sur Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Medicina de Precisión / Aprendizaje Profundo / Neoplasias / Antineoplásicos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2018 Tipo del documento: Article País de afiliación: Corea del Sur Pais de publicación: Reino Unido