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Predicting the causative pathogen among children with pneumonia using a causal Bayesian network.

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Title: Predicting the causative pathogen among children with pneumonia using a causal Bayesian network.
Authors: Wu, Yue1,2 (AUTHOR) yue.wu1@sydney.edu.au, Mascaro, Steven3,4 (AUTHOR), Bhuiyan, Mejbah2 (AUTHOR), Fathima, Parveen1 (AUTHOR), Mace, Ariel O.2,5,6 (AUTHOR), Nicol, Mark P.7 (AUTHOR), Richmond, Peter C.2,5,8 (AUTHOR), Kirkham, Lea-Ann2 (AUTHOR), Dymock, Michael2 (AUTHOR), Foley, David A.2,9 (AUTHOR), McLeod, Charlie2,10 (AUTHOR), Borland, Meredith L.8,11 (AUTHOR), Martin, Andrew5 (AUTHOR), Williams, Phoebe C. M.1,12,13 (AUTHOR), Marsh, Julie A.2 (AUTHOR), Snelling, Thomas L.1,2,12,14,15 (AUTHOR), Blyth, Christopher C.2,8,9,10 (AUTHOR)
Source: PLoS Computational Biology. 3/13/2023, Vol. 19 Issue 3, p1-25. 25p. 7 Diagrams, 4 Charts, 2 Graphs.
Database: Academic Search Ultimate
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  Data: <searchLink fieldCode="JN" term="%22PLoS+Computational+Biology%22">PLoS Computational Biology</searchLink>. 3/13/2023, Vol. 19 Issue 3, p1-25. 25p. 7 Diagrams, 4 Charts, 2 Graphs.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=162398108
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              Text: 3/13/2023
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