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[Application of support vector machine in predicting in-hospital mortality risk of patients with acute kidney injury in ICU].
Lin, K; Xie, J Q; Hu, Y H; Kong, G L.
  • Lin K; Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China; Medical Informatics Center, Peking University, Beijing 100191, China.
  • Xie JQ; Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China; Medical Informatics Center, Peking University, Beijing 100191, China.
  • Hu YH; Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China; Medical Informatics Center, Peking University, Beijing 100191, China.
  • Kong GL; Medical Informatics Center, Peking University, Beijing 100191, China.
Beijing Da Xue Xue Bao Yi Xue Ban ; 50(2): 239-244, 2018 Apr 18.
Article en Zh | MEDLINE | ID: mdl-29643521
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Banco de datos: MEDLINE Asunto principal: Mortalidad Hospitalaria / Lesión Renal Aguda / Máquina de Vectores de Soporte Tipo de estudio: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: Zh Año: 2018 Tipo del documento: Article
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PubMed Links

Banco de datos: MEDLINE Asunto principal: Mortalidad Hospitalaria / Lesión Renal Aguda / Máquina de Vectores de Soporte Tipo de estudio: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: Zh Año: 2018 Tipo del documento: Article