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Using a machine learning model to predict the development of acute kidney injury in patients with heart failure.
Liu, Wen Tao; Liu, Xiao Qi; Jiang, Ting Ting; Wang, Meng Ying; Huang, Yang; Huang, Yu Lin; Jin, Feng Yong; Zhao, Qing; Wu, Qin Yi; Liu, Bi Cheng; Ruan, Xiong Zhong; Ma, Kun Ling.
Afiliação
  • Liu WT; School of Medicine, Institute of Nephrology, Zhongda Hospital, Southeast University, Nanjing, China.
  • Liu XQ; School of Medicine, Institute of Nephrology, Zhongda Hospital, Southeast University, Nanjing, China.
  • Jiang TT; School of Medicine, Institute of Nephrology, Zhongda Hospital, Southeast University, Nanjing, China.
  • Wang MY; School of Medicine, Institute of Nephrology, Zhongda Hospital, Southeast University, Nanjing, China.
  • Huang Y; School of Medicine, Institute of Nephrology, Zhongda Hospital, Southeast University, Nanjing, China.
  • Huang YL; School of Medicine, Institute of Nephrology, Zhongda Hospital, Southeast University, Nanjing, China.
  • Jin FY; School of Medicine, Institute of Nephrology, Zhongda Hospital, Southeast University, Nanjing, China.
  • Zhao Q; School of Medicine, Institute of Nephrology, Zhongda Hospital, Southeast University, Nanjing, China.
  • Wu QY; School of Medicine, Institute of Nephrology, Zhongda Hospital, Southeast University, Nanjing, China.
  • Liu BC; School of Medicine, Institute of Nephrology, Zhongda Hospital, Southeast University, Nanjing, China.
  • Ruan XZ; John Moorhead Research Laboratory, Department of Renal Medicine, University College London (UCL) Medical School, London, United Kingdom.
  • Ma KL; Department of Nephrology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Front Cardiovasc Med ; 9: 911987, 2022.
Article em En | MEDLINE | ID: mdl-36176988
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Cardiovasc Med Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Cardiovasc Med Ano de publicação: 2022 Tipo de documento: Article