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1.
Clinical phenotypes and outcomes of SARS-CoV-2, influenza, RSV and seven other respiratory viruses: a retrospective study using complete hospital data.
Thorax
; 77(2): 154-163, 2022 02.
Artículo
en Inglés
| MEDLINE | ID: mdl-34226206
2.
SARS-CoV-2 testing in patients with low COVID-19 suspicion at admission to a tertiary care hospital, Stockholm, Sweden, March to September 2020.
Euro Surveill
; 27(7)2022 02.
Artículo
en Inglés
| MEDLINE | ID: mdl-35177168
3.
The accuracy of fully-automated algorithms for the surveillance of central venous catheter-related bloodstream infection in hospitalised patients.
Antimicrob Resist Infect Control
; 13(1): 15, 2024 02 05.
Artículo
en Inglés
| MEDLINE | ID: mdl-38317207
4.
Predicting sepsis onset using a machine learned causal probabilistic network algorithm based on electronic health records data.
Sci Rep
; 13(1): 11760, 2023 07 20.
Artículo
en Inglés
| MEDLINE | ID: mdl-37474597
5.
The accuracy of fully automated algorithms for surveillance of healthcare-onset Clostridioides difficile infections in hospitalized patients.
Antimicrob Steward Healthc Epidemiol
; 2(1): e43, 2022.
Artículo
en Inglés
| MEDLINE | ID: mdl-36310782
6.
Validation of automated sepsis surveillance based on the Sepsis-3 clinical criteria against physician record review in a general hospital population: observational study using electronic health records data.
BMJ Qual Saf
; 29(9): 735-745, 2020 09.
Artículo
en Inglés
| MEDLINE | ID: mdl-32029574
7.
Detecting hospital-acquired infections: A document classification approach using support vector machines and gradient tree boosting.
Health Informatics J
; 24(1): 24-42, 2018 03.
Artículo
en Inglés
| MEDLINE | ID: mdl-27496862
8.
Detection of healthcare-associated urinary tract infection in Swedish electronic health records.
Stud Health Technol Inform
; 207: 330-9, 2014.
Artículo
en Inglés
| MEDLINE | ID: mdl-25488239
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