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Using Machine Learning to Identify Metabolomic Signatures of Pediatric Chronic Kidney Disease Etiology.
Lee, Arthur M; Hu, Jian; Xu, Yunwen; Abraham, Alison G; Xiao, Rui; Coresh, Josef; Rebholz, Casey; Chen, Jingsha; Rhee, Eugene P; Feldman, Harold I; Ramachandran, Vasan S; Kimmel, Paul L; Warady, Bradley A; Furth, Susan L; Denburg, Michelle R.
Afiliação
  • Lee AM; Division of Nephrology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
  • Hu J; Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania.
  • Xu Y; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore Maryland.
  • Abraham AG; School of Public Health, University of Colorado Denver, Denver, Colorado.
  • Xiao R; Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania.
  • Coresh J; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore Maryland.
  • Rebholz C; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore Maryland.
  • Chen J; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore Maryland.
  • Rhee EP; Department of Medicine, Massachusetts General Hospital, Harvard University, Boston, Massachusetts.
  • Feldman HI; Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania.
  • Ramachandran VS; Department of Medicine, Boston University School of Medicine, Boston University School of Public Health, Boston University Center for Computing and Data Science, Boston, Massachusetts.
  • Kimmel PL; National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland.
  • Warady BA; Department of Pediatrics, Children's Mercy Hospital, University of Missouri-Kansas City School of Medicine, Kansas City, Missouri.
  • Furth SL; Division of Nephrology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
  • Denburg MR; Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania.
J Am Soc Nephrol ; 33(2): 375-386, 2022 02.
Article em En | MEDLINE | ID: mdl-35017168
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Insuficiência Renal Crônica / Metaboloma / Metabolômica / Aprendizado de Máquina Tipo de estudo: Clinical_trials / Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Child / Child, preschool / Female / Humans / Infant / Male Idioma: En Revista: J Am Soc Nephrol Assunto da revista: NEFROLOGIA Ano de publicação: 2022 Tipo de documento: Article
Texto completo
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PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Insuficiência Renal Crônica / Metaboloma / Metabolômica / Aprendizado de Máquina Tipo de estudo: Clinical_trials / Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Child / Child, preschool / Female / Humans / Infant / Male Idioma: En Revista: J Am Soc Nephrol Assunto da revista: NEFROLOGIA Ano de publicação: 2022 Tipo de documento: Article