Personalized ICU mortality assessment by interpretable machine learning algorithms in patients with sepsis combined lung cancer: a population-based study and an external validation cohort.

Tang H, Hao H, Han Y.

Open source

DOI: 10.3389/fonc.2025.1661212
Published: 2025-10-01
Container: Front Oncol
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/fonc.2025.1661212,
  title = {Personalized ICU mortality assessment by interpretable machine learning algorithms in patients with sepsis combined lung cancer: a population-based study and an external validation cohort.},
  author = {Tang H and  Hao H and  Han Y.},
  year = {2025},
  journal = {Front Oncol},
  doi = {10.3389/fonc.2025.1661212},
  url = {https://doi.org/10.3389/fonc.2025.1661212}
}

RIS

TY  - JOUR
TI  - Personalized ICU mortality assessment by interpretable machine learning algorithms in patients with sepsis combined lung cancer: a population-based study and an external validation cohort.
AU  - Tang H
AU  -  Hao H
AU  -  Han Y.
PY  - 2025
JO  - Front Oncol
DO  - 10.3389/fonc.2025.1661212
UR  - https://doi.org/10.3389/fonc.2025.1661212
ER  -

APA

H, T., H, H., & Y., H. (2025). Personalized ICU mortality assessment by interpretable machine learning algorithms in patients with sepsis combined lung cancer: a population-based study and an external validation cohort.. Front Oncol. https://doi.org/10.3389/fonc.2025.1661212

Source records

europe-pmc · retrieved 2026-09-26T21:09:53.317Z
doaj · retrieved 2026-09-26T21:09:53.324Z