Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score

Research output: Contribution to journal › Article (Academic Journal) › peer-review

24 Citations (Scopus)

Original language	English
Journal	British Journal of Surgery
DOIs	https://doi.org/10.1093/bjs/znab183 https://doi.org/10.1093/bjs/znab183
Publication status	Published - 6 Jul 2021

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@article{07b59ee1f5294c7a8496675535ad0975,

title = "Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score",

author = "\{COVIDSurg Collaborative\} and James Olivier and Fairhurst, \{Katherine J\} and Lawday, \{Sam D J\}",

year = "2021",

month = jul,

day = "6",

doi = "10.1093/bjs/znab183",

language = "English",

journal = "British Journal of Surgery",

issn = "0007-1323",

publisher = "Oxford University Press",

}

TY - JOUR

T1 - Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score

AU - COVIDSurg Collaborative

AU - Olivier, James

AU - Fairhurst, Katherine J

AU - Lawday, Sam D J

PY - 2021/7/6

Y1 - 2021/7/6

UR - http://europepmc.org/abstract/med/34227657

U2 - 10.1093/bjs/znab183

DO - 10.1093/bjs/znab183

M3 - Article (Academic Journal)

C2 - 34227657

SN - 0007-1323

JO - British Journal of Surgery

JF - British Journal of Surgery

ER -