Machine learning-based prediction of bloodstream infection in rectal carbapenem-resistant Enterobacterales carriers: a multicenter retrospective cohort study.

Jeon K, Song W, Shin DH, Kim HS, Kim HS, Lee J, Jeong SH, Jeong S

Open source

DOI
10.3389/fcimb.2026.1791859
Published
2026
Container
Frontiers in cellular and infection microbiology
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.3389/fcimb.2026.1791859,
  title = {Machine learning-based prediction of bloodstream infection in rectal carbapenem-resistant Enterobacterales carriers: a multicenter retrospective cohort study.},
  author = {Jeon K and Song W and Shin DH and Kim HS and Kim HS and Lee J and Jeong SH and Jeong S},
  year = {2026},
  journal = {Frontiers in cellular and infection microbiology},
  doi = {10.3389/fcimb.2026.1791859},
  url = {https://doi.org/10.3389/fcimb.2026.1791859}
}

RIS

TY  - JOUR
TI  - Machine learning-based prediction of bloodstream infection in rectal carbapenem-resistant Enterobacterales carriers: a multicenter retrospective cohort study.
AU  - Jeon K
AU  - Song W
AU  - Shin DH
AU  - Kim HS
AU  - Kim HS
AU  - Lee J
AU  - Jeong SH
AU  - Jeong S
PY  - 2026
JO  - Frontiers in cellular and infection microbiology
DO  - 10.3389/fcimb.2026.1791859
UR  - https://doi.org/10.3389/fcimb.2026.1791859
ER  - 

APA

K, J., W, S., DH, S., HS, K., HS, K., J, L., SH, J., & S, J. (2026). Machine learning-based prediction of bloodstream infection in rectal carbapenem-resistant Enterobacterales carriers: a multicenter retrospective cohort study.. Frontiers in cellular and infection microbiology. https://doi.org/10.3389/fcimb.2026.1791859

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