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Prediction Models for the Clinical Severity of Patients With COVID-19 in Korea: Retrospective Multicenter Cohort Study.
Oh, Bumjo; Hwangbo, Suhyun; Jung, Taeyeong; Min, Kyungha; Lee, Chanhee; Apio, Catherine; Lee, Hyejin; Lee, Seungyeoun; Moon, Min Kyong; Kim, Shin-Woo; Park, Taesung.
Afiliación
  • Oh B; Department of Family Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, Republic of Korea.
  • Hwangbo S; Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
  • Jung T; Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
  • Min K; Department of Family Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, Republic of Korea.
  • Lee C; Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
  • Apio C; Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
  • Lee H; Department of Family Medicine, Seoul National University Bundang Hospital, Gyeonggi-do, Republic of Korea.
  • Lee S; Department of Mathematics and Statistics, Sejong University, Seoul, Republic of Korea.
  • Moon MK; Department of Internal Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, Republic of Korea.
  • Kim SW; Department of Internal Medicine, Kyungpook National University, Daegu, Republic of Korea.
  • Park T; Department of Statistics, Seoul National University, Seoul, Republic of Korea.
J Med Internet Res ; 23(4): e25852, 2021 04 16.
Article en En | MEDLINE | ID: mdl-33822738
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Modelos Estadísticos / COVID-19 Tipo de estudio: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adolescent / Adult / Aged / Aged80 / Child / Child, preschool / Female / Humans / Infant / Male País/Región como asunto: Asia Idioma: En Revista: J Med Internet Res Asunto de la revista: INFORMATICA MEDICA Año: 2021 Tipo del documento: Article
Texto completo
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Modelos Estadísticos / COVID-19 Tipo de estudio: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adolescent / Adult / Aged / Aged80 / Child / Child, preschool / Female / Humans / Infant / Male País/Región como asunto: Asia Idioma: En Revista: J Med Internet Res Asunto de la revista: INFORMATICA MEDICA Año: 2021 Tipo del documento: Article