Under the background of the new global definition of ARDS: an interpretable machine learning approach for predicting 28-day ICU mortality in patients with sepsis complicated by ARDS
The application of machine learning methodologies to construct prognostic prediction models for sepsis patients complicated by ARDS, informed by the new global definition, proves to be reliable. This approach can assist clinicians in developing personalized treatment strategies for affected patients.
Authors
- Hui Peng (ORCID: https://orcid.org/0000-0002-7673-3919)
- Haiquan Li (ORCID: https://orcid.org/0000-0002-8049-0278)
- Lei Lv (ORCID: https://orcid.org/0000-0001-6153-1153)
- Shuo Yuan (ORCID: https://orcid.org/0009-0008-9459-5901)
- Shuzhan Zhang (ORCID: https://orcid.org/0000-0002-1579-6262)
- Peijie Zhang
- Zi Ye (ORCID: https://orcid.org/0000-0003-1846-2572)
- Ningjun Zhao
- Zhe Yuan (ORCID: https://orcid.org/0000-0002-3713-7479)
- Hongning Yang
Institutions
- Xuzhou Medical College (CN)
- Second Affiliated Hospital of Xuzhou Medical College (CN)
- Xuzhou No.1 People's Hospital (CN)
Publication Details
- Journal
- Frontiers in Physiology
- Published
- 2025-09-19
- DOI
- https://doi.org/10.3389/fphys.2025.1617196
- Citations
- 3
- Primary Topic
- Sepsis Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 4.06