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DLMM as a lossless one-shot algorithm for collaborative multi-site distributed linear mixed models.
Luo, Chongliang; Islam, Md Nazmul; Sheils, Natalie E; Buresh, John; Reps, Jenna; Schuemie, Martijn J; Ryan, Patrick B; Edmondson, Mackenzie; Duan, Rui; Tong, Jiayi; Marks-Anglin, Arielle; Bian, Jiang; Chen, Zhaoyi; Duarte-Salles, Talita; Fernández-Bertolín, Sergio; Falconer, Thomas; Kim, Chungsoo; Park, Rae Woong; Pfohl, Stephen R; Shah, Nigam H; Williams, Andrew E; Xu, Hua; Zhou, Yujia; Lautenbach, Ebbing; Doshi, Jalpa A; Werner, Rachel M; Asch, David A; Chen, Yong.
Afiliação
  • Luo C; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
  • Islam MN; Division of Public Health Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, USA.
  • Sheils NE; Optum Labs, Minnetonka, MN, USA.
  • Buresh J; Optum Labs, Minnetonka, MN, USA.
  • Reps J; Optum Labs, Minnetonka, MN, USA.
  • Schuemie MJ; Janssen Research and Development LLC, Titusville, NJ, USA.
  • Ryan PB; Janssen Research and Development LLC, Titusville, NJ, USA.
  • Edmondson M; Janssen Research and Development LLC, Titusville, NJ, USA.
  • Duan R; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
  • Tong J; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
  • Marks-Anglin A; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Bian J; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
  • Chen Z; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
  • Duarte-Salles T; Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA.
  • Fernández-Bertolín S; Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA.
  • Falconer T; Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain.
  • Kim C; Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain.
  • Park RW; Department of Biomedical Informatics, Columbia University, New York, NY, USA.
  • Pfohl SR; Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Republic of Korea.
  • Shah NH; Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Republic of Korea.
  • Williams AE; Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Republic of Korea.
  • Xu H; Stanford Center for Biomedical Informatics Research, Stanford, CA, USA.
  • Zhou Y; Stanford Center for Biomedical Informatics Research, Stanford, CA, USA.
  • Lautenbach E; Institute for Clinical Research and Health Policy Studies, Tufts University School of Medicine, Boston, MA, USA.
  • Doshi JA; School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Werner RM; School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Asch DA; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
  • Chen Y; Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Nat Commun ; 13(1): 1678, 2022 03 30.
Article em En | MEDLINE | ID: mdl-35354802
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Nat Commun Assunto da revista: BIOLOGIA / CIENCIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Nat Commun Assunto da revista: BIOLOGIA / CIENCIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos