Development and Validation of an Interpretable Machine Learning Model to Predict Mortality in Patients With Sepsis-Induced Coagulopathy: Multicenter Cohort Study.
- DOI
- 10.2196/90285
- Published
- 2026 Sep 21
- Container
- JMIR medical informatics
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.2196/90285,
title = {Development and Validation of an Interpretable Machine Learning Model to Predict Mortality in Patients With Sepsis-Induced Coagulopathy: Multicenter Cohort Study.},
author = {Sun J and Wang J and Dong Y and Liu J and Ding Y and Fan S and Chen D and Shou S},
year = {2026},
journal = {JMIR medical informatics},
doi = {10.2196/90285},
url = {https://doi.org/10.2196/90285}
}RIS
TY - JOUR TI - Development and Validation of an Interpretable Machine Learning Model to Predict Mortality in Patients With Sepsis-Induced Coagulopathy: Multicenter Cohort Study. AU - Sun J AU - Wang J AU - Dong Y AU - Liu J AU - Ding Y AU - Fan S AU - Chen D AU - Shou S PY - 2026 JO - JMIR medical informatics DO - 10.2196/90285 UR - https://doi.org/10.2196/90285 ER -
APA
J, S., J, W., Y, D., J, L., Y, D., S, F., D, C., & S, S. (2026). Development and Validation of an Interpretable Machine Learning Model to Predict Mortality in Patients With Sepsis-Induced Coagulopathy: Multicenter Cohort Study.. JMIR medical informatics. https://doi.org/10.2196/90285
Source records
- pubmed · retrieved 2026-09-24T22:11:57.088Z