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Predicting postoperative surgical site infection with administrative data: a random forests algorithm.

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Title: Predicting postoperative surgical site infection with administrative data: a random forests algorithm.
Authors: Petrosyan, Yelena1 (AUTHOR), Thavorn, Kednapa1,2,3,4 (AUTHOR) kthavorn@ohri.ca, Smith, Glenys3 (AUTHOR), Maclure, Malcolm5 (AUTHOR), Preston, Roanne5 (AUTHOR), van Walravan, Carl1,2,3 (AUTHOR), Forster, Alan J.1,3,6 (AUTHOR)
Source: BMC Medical Research Methodology. 8/28/2021, Vol. 21 Issue 1, p1-11. 11p.
Database: Academic Search Ultimate
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  Data: <searchLink fieldCode="JN" term="%22BMC+Medical+Research+Methodology%22">BMC Medical Research Methodology</searchLink>. 8/28/2021, Vol. 21 Issue 1, p1-11. 11p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=152168321
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        Value: 10.1186/s12874-021-01369-9
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        Text: English
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      – TitleFull: Predicting postoperative surgical site infection with administrative data: a random forests algorithm.
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              Text: 8/28/2021
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              Y: 2021
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