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

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Bibliographic Details
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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Description
ISSN:03424642
DOI:10.1007/s00134-023-07137-1