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Predicting Mortality Using Machine Learning Algorithms in Patients Who Require Renal Replacement Therapy in the Critical Care Unit.
Chang, Hsin-Hsiung; Chiang, Jung-Hsien; Wang, Chi-Shiang; Chiu, Ping-Fang; Abdel-Kader, Khaled; Chen, Huiwen; Siew, Edward D; Yabes, Jonathan; Murugan, Raghavan; Clermont, Gilles; Palevsky, Paul M; Jhamb, Manisha.
Afiliação
  • Chang HH; Division of Nephrology, Department of Internal Medicine, Antai Medical Care Corporation Antai Tian-Sheng Memorial Hospital, Donggang 928, Taiwan.
  • Chiang JH; Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan.
  • Wang CS; Renal-Electrolyte Division, Department of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
  • Chiu PF; Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan.
  • Abdel-Kader K; Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan.
  • Chen H; Division of Nephrology, Department of Internal Medicine, Changhua Christian Hospital, Changhua 500, Taiwan.
  • Siew ED; Department of Hospitality Management, MingDao University, Changhua 500, Taiwan.
  • Yabes J; Division of Nephrology and Hypertension, Vanderbilt University Medical Center, Nashville, TN 37011, USA.
  • Murugan R; Vanderbilt Center for Kidney Disease (VCKD) and Integrated Program for AKI Research (VIP-AKI), Nashville, TN 37011, USA.
  • Clermont G; Renal-Electrolyte Division, Department of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
  • Palevsky PM; Division of Nephrology and Hypertension, Vanderbilt University Medical Center, Nashville, TN 37011, USA.
  • Jhamb M; Vanderbilt Center for Kidney Disease (VCKD) and Integrated Program for AKI Research (VIP-AKI), Nashville, TN 37011, USA.
J Clin Med ; 11(18)2022 Sep 08.
Article em En | MEDLINE | ID: mdl-36142936

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article