Real-time prediction of cardiorespiratory deterioration during paediatric critical care transport using interpretable machine learning

Milan Kapur, Kezhi Li, Alexander Brown, Zhiqiang Huo, John Booth, Philip Knight, Gwyneth Davies, Padmanabhan Ramnarayan

Open source

DOI: 10.1371/journal.pdig.0001410
Published: 2026-05-19
Container: PLOS Digital Health
Publisher: Public Library of Science (PLoS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pdig.0001410,
  title = {Real-time prediction of cardiorespiratory deterioration during paediatric critical care transport using interpretable machine learning},
  author = {Milan Kapur and Kezhi Li and Alexander Brown and Zhiqiang Huo and John Booth and Philip Knight and Gwyneth Davies and Padmanabhan Ramnarayan},
  year = {2026},
  journal = {PLOS Digital Health},
  doi = {10.1371/journal.pdig.0001410},
  url = {https://doi.org/10.1371/journal.pdig.0001410}
}

RIS

TY  - JOUR
TI  - Real-time prediction of cardiorespiratory deterioration during paediatric critical care transport using interpretable machine learning
AU  - Milan Kapur
AU  - Kezhi Li
AU  - Alexander Brown
AU  - Zhiqiang Huo
AU  - John Booth
AU  - Philip Knight
AU  - Gwyneth Davies
AU  - Padmanabhan Ramnarayan
PY  - 2026
JO  - PLOS Digital Health
DO  - 10.1371/journal.pdig.0001410
UR  - https://doi.org/10.1371/journal.pdig.0001410
ER  -

APA

Kapur, M., Li, K., Brown, A., Huo, Z., Booth, J., Knight, P., Davies, G., & Ramnarayan, P. (2026). Real-time prediction of cardiorespiratory deterioration during paediatric critical care transport using interpretable machine learning. PLOS Digital Health. https://doi.org/10.1371/journal.pdig.0001410

Source records

crossref · retrieved 2026-09-26T22:53:54.255Z