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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.
Affiliation
  • 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 in Zh | MEDLINE | ID: mdl-29643521
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Collection: 01-internacional Database: MEDLINE Main subject: Hospital Mortality / Acute Kidney Injury / Support Vector Machine Type of study: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: Zh Journal: Beijing Da Xue Xue Bao Yi Xue Ban Journal subject: MEDICINA Year: 2018 Document type: Article Affiliation country: China Country of publication: China
Search on Google
Add to My VHL
Print
XML
PubMed Links

Collection: 01-internacional Database: MEDLINE Main subject: Hospital Mortality / Acute Kidney Injury / Support Vector Machine Type of study: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: Zh Journal: Beijing Da Xue Xue Bao Yi Xue Ban Journal subject: MEDICINA Year: 2018 Document type: Article Affiliation country: China Country of publication: China