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Deep learning predicts the differentiation of kidney organoids derived from human induced pluripotent stem cells.
Park, Keonhyeok; Lee, Jong Young; Lee, Soo Young; Jeong, Iljoo; Park, Seo-Yeon; Kim, Jin Won; Nam, Sun Ah; Kim, Hyung Wook; Kim, Yong Kyun; Lee, Seungchul.
Afiliação
  • Park K; Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Republic of Korea.
  • Lee JY; Cell Death Disease Research Center, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Lee SY; Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Republic of Korea.
  • Jeong I; Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Republic of Korea.
  • Park SY; Cell Death Disease Research Center, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Kim JW; Cell Death Disease Research Center, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Nam SA; Cell Death Disease Research Center, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Kim HW; Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Suwon, Republic of Korea.
  • Kim YK; Cell Death Disease Research Center, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Lee S; Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Suwon, Republic of Korea.
Kidney Res Clin Pract ; 42(1): 75-85, 2023 Jan.
Article em En | MEDLINE | ID: mdl-36328994
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Kidney Res Clin Pract Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Kidney Res Clin Pract Ano de publicação: 2023 Tipo de documento: Article