Your browser doesn't support javascript.
loading
Machine learning algorithm to predict mortality in critically ill patients with sepsis-associated acute kidney injury.
Li, Xunliang; Wu, Ruijuan; Zhao, Wenman; Shi, Rui; Zhu, Yuyu; Wang, Zhijuan; Pan, Haifeng; Wang, Deguang.
Afiliación
  • Li X; Department of Nephrology, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, People's Republic of China.
  • Wu R; Institute of Kidney Disease, Inflammation and Immunity Mediated Diseases, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, People's Republic of China.
  • Zhao W; Department of Nephrology, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, People's Republic of China.
  • Shi R; Institute of Kidney Disease, Inflammation and Immunity Mediated Diseases, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, People's Republic of China.
  • Zhu Y; Department of Nephrology, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, People's Republic of China.
  • Wang Z; Institute of Kidney Disease, Inflammation and Immunity Mediated Diseases, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, People's Republic of China.
  • Pan H; Department of Nephrology, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, People's Republic of China.
  • Wang D; Institute of Kidney Disease, Inflammation and Immunity Mediated Diseases, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, People's Republic of China.
Sci Rep ; 13(1): 5223, 2023 03 30.
Article en En | MEDLINE | ID: mdl-36997585
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: Sepsis / Lesión Renal Aguda Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Female / Humans / Male Idioma: En Revista: Sci Rep Año: 2023 Tipo del documento: Article Pais de publicación: Reino Unido
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: Sepsis / Lesión Renal Aguda Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Female / Humans / Male Idioma: En Revista: Sci Rep Año: 2023 Tipo del documento: Article Pais de publicación: Reino Unido