Machine Learning Prediction and Causal Forest Analysis of Severe Acute Kidney Injury in ICU Patients with COPD: A MIMIC-IV Study
LiFeng Fang, Fei Wang, Junkang Chen, Yulong Zheng · 2026
Read Machine Learning Prediction and Causal Forest Analysis of Severe Acute Kidney Injury in ICU Patients with COPD: A MIMIC-IV Study by LiFeng Fang, Fei Wang, Junkang Chen, Yulong Zheng (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13589527.txt.
Description
LiFeng Fang, Fei Wang, Junkang Chen, and Yulong Zheng model severe kidney injury in intensive care patients with lung disease in a 2026 paper. Severe kidney injury is common in this group, but a factor that predicts harm is not thereby a cause. The team build prediction models from a large critical care database and then probe causal effects with care.
A first model sorted cases well but used the full stay length, so it reads as a record of the course rather than an early warning. A stricter test that only uses data from the first day scored much lower. The authors stress that split as the study's lesson, and call for outside validation.
Catalog record
| CREATOR | LiFeng Fang, Fei Wang, Junkang Chen, Yulong Zheng |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 68 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |