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Modeling COVID-19 disease processes by remote elicitation of causal Bayesian networks from medical experts.
Mascaro, Steven; Wu, Yue; Woodberry, Owen; Nyberg, Erik P; Pearson, Ross; Ramsay, Jessica A; Mace, Ariel O; Foley, David A; Snelling, Thomas L; Nicholson, Ann E.
Afiliação
  • Mascaro S; Faculty of Information Technology, Monash University, Clayton, VIC 3168, Australia.
  • Wu Y; Bayesian Intelligence Pty Ltd, Upwey, VIC 3158, Australia.
  • Woodberry O; School of Public Health, University of Sydney, Camperdown, NSW 2006, Australia.
  • Nyberg EP; Faculty of Information Technology, Monash University, Clayton, VIC 3168, Australia.
  • Pearson R; Bayesian Intelligence Pty Ltd, Upwey, VIC 3158, Australia.
  • Ramsay JA; Faculty of Information Technology, Monash University, Clayton, VIC 3168, Australia.
  • Mace AO; Faculty of Information Technology, Monash University, Clayton, VIC 3168, Australia.
  • Foley DA; Wesfarmers Centre of Vaccines and Infectious Diseases, Telethon Kids Institute, University of Western Australia, Nedlands, WA 6009, Australia.
  • Snelling TL; Wesfarmers Centre of Vaccines and Infectious Diseases, Telethon Kids Institute, University of Western Australia, Nedlands, WA 6009, Australia.
  • Nicholson AE; Department of General Paediatrics, Perth Children's Hospital, Nedlands, WA 6009, Australia.
BMC Med Res Methodol ; 23(1): 76, 2023 03 29.
Article em En | MEDLINE | ID: mdl-36991342
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: COVID-19 Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: COVID-19 Idioma: En Ano de publicação: 2023 Tipo de documento: Article