Development of interpretable machine learning models for predicting the probability of sepsis in patients with pulmonary fibrosis in the intensive care unit: based on MIMIC-IV and multi-database validation.
- DOI
- 10.3389/fcimb.2026.1894489
- Published
- 2026
- Container
- Frontiers in cellular and infection microbiology
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3389/fcimb.2026.1894489,
title = {Development of interpretable machine learning models for predicting the probability of sepsis in patients with pulmonary fibrosis in the intensive care unit: based on MIMIC-IV and multi-database validation.},
author = {Xia Y and Yang J},
year = {2026},
journal = {Frontiers in cellular and infection microbiology},
doi = {10.3389/fcimb.2026.1894489},
url = {https://doi.org/10.3389/fcimb.2026.1894489}
}RIS
TY - JOUR TI - Development of interpretable machine learning models for predicting the probability of sepsis in patients with pulmonary fibrosis in the intensive care unit: based on MIMIC-IV and multi-database validation. AU - Xia Y AU - Yang J PY - 2026 JO - Frontiers in cellular and infection microbiology DO - 10.3389/fcimb.2026.1894489 UR - https://doi.org/10.3389/fcimb.2026.1894489 ER -
APA
Y, X., & J, Y. (2026). Development of interpretable machine learning models for predicting the probability of sepsis in patients with pulmonary fibrosis in the intensive care unit: based on MIMIC-IV and multi-database validation.. Frontiers in cellular and infection microbiology. https://doi.org/10.3389/fcimb.2026.1894489
Source records
- pubmed · retrieved 2026-09-25T09:32:53.178Z