Your browser doesn't support javascript.
loading
High-Throughput Algorithm for Discovering New Drug Indications by Utilizing Large-Scale Electronic Medical Record Data.
Kim, Do-Hoon; Lee, Jung-Eun; Kim, Yong-Gil; Lee, Yura; Seo, Dong-Woo; Lee, Kye Hwa; Lee, Jae-Ho; Kim, Woo Sung; Kim, Young-Hak; Oh, Ji Seon.
Afiliación
  • Kim DH; Department of Information Medicine, Asan Medical Center, Seoul, Republic of Korea.
  • Lee JE; Asan Institute for Life Sciences, Asan Medical Center, Seoul, Republic of Korea.
  • Kim YG; Division of Rheumatology, Department of Internal Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Lee Y; Department of Information Medicine, Asan Medical Center, Seoul, Republic of Korea.
  • Seo DW; Department of Information Medicine, Asan Medical Center, Seoul, Republic of Korea.
  • Lee KH; Department of Emergency Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Lee JH; Department of Information Medicine, Asan Medical Center, Seoul, Republic of Korea.
  • Kim WS; Department of Information Medicine, Asan Medical Center, Seoul, Republic of Korea.
  • Kim YH; Department of Emergency Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Oh JS; Department of Information Medicine, Asan Medical Center, Seoul, Republic of Korea.
Clin Pharmacol Ther ; 108(6): 1299-1307, 2020 12.
Article en En | MEDLINE | ID: mdl-32621536
Asunto(s)
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Registros Electrónicos de Salud / Minería de Datos / Reposicionamiento de Medicamentos / Hipoglucemiantes / Hipolipemiantes Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Clin Pharmacol Ther Año: 2020 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Registros Electrónicos de Salud / Minería de Datos / Reposicionamiento de Medicamentos / Hipoglucemiantes / Hipolipemiantes Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Clin Pharmacol Ther Año: 2020 Tipo del documento: Article Pais de publicación: Estados Unidos