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Machine Learning Predicts Acute Kidney Injury in Hospitalized Patients with Sickle Cell Disease.
Zahr, Rima S; Mohammed, Akram; Naik, Surabhi; Faradji, Daniel; Ataga, Kenneth I; Lebensburger, Jeffrey; Davis, Robert L.
Afiliación
  • Zahr RS; Division of Pediatric Nephrology and Hypertension, University of Tennessee Health Science Center Memphis, Memphis, Tennessee, USA.
  • Mohammed A; Center for Biomedical Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
  • Naik S; Department of Surgery, University of Tennessee Health Sciences Center, Memphis, Tennessee, USA.
  • Faradji D; College of Medicine, University of Tennessee Health Sciences Center, Memphis, Tennessee, USA.
  • Ataga KI; Center for Sickle Cell Disease, University of Tennessee Health Sciences Center, Memphis, Tennessee, USA.
  • Lebensburger J; Division of Pediatric Hematology and Oncology, University of Alabama at Birmingham, Birmingham, Alabama, USA.
  • Davis RL; Center for Biomedical Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
Am J Nephrol ; 55(1): 18-24, 2024.
Article en En | MEDLINE | ID: mdl-37906980
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Lesión Renal Aguda / Anemia de Células Falciformes Límite: Adult / Female / Humans / Male Idioma: En Revista: Am J Nephrol Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Lesión Renal Aguda / Anemia de Células Falciformes Límite: Adult / Female / Humans / Male Idioma: En Revista: Am J Nephrol Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos