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Machine learning to predict poor school performance in paediatric survivors of intensive care: a population-based cohort study.

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Title: Machine learning to predict poor school performance in paediatric survivors of intensive care: a population-based cohort study.
Authors: Gilholm, Patricia1 (AUTHOR), Gibbons, Kristen1 (AUTHOR), Brüningk, Sarah2,3 (AUTHOR), Klatt, Juliane2,3 (AUTHOR), Vaithianathan, Rhema4 (AUTHOR), Long, Debbie1,5 (AUTHOR), Millar, Johnny6,7,8 (AUTHOR), Tomaszewski, Wojtek4 (AUTHOR), Schlapbach, Luregn J.1,9 (AUTHOR) luregn.schlapbach@kispi.uzh.ch, the Australian and New Zealand Intensive Care Society (ANZICS) Centre for Outcomes and Resource Evaluation (CORE) and ANZICS Paediatric Study Group (ANZICS PSG) (AUTHOR), Ganeshalingam, Anusha (AUTHOR), Sherring, Claire (AUTHOR), Erickson, Simon (AUTHOR), Barr, Samantha (AUTHOR), Raman, Sainath (AUTHOR), Schlapbach, Luregn (AUTHOR), George, Shane (AUTHOR), Singh, Puneet (AUTHOR), Smith, Vicky (AUTHOR), Butt, Warwick (AUTHOR)
Source: Intensive Care Medicine. Jul2023, Vol. 49 Issue 7, p785-795. 11p. 1 Diagram, 2 Charts, 2 Graphs.
Database: Academic Search Ultimate
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  Data: <searchLink fieldCode="JN" term="%22Intensive+Care+Medicine%22">Intensive Care Medicine</searchLink>. Jul2023, Vol. 49 Issue 7, p785-795. 11p. 1 Diagram, 2 Charts, 2 Graphs.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=164982963
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              Text: Jul2023
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