The pan-immune-inflammation value predicts stroke-associated pneumonia and poor outcome in spontaneous intracerebral hemorrhage: a machine learning approach
Anni Chen, Jiahui Wang, Qiaoying Huang, Chaoxiong Shen, Zhizhou Hu, Xiaohong Hu · 2026
Read The pan-immune-inflammation value predicts stroke-associated pneumonia and poor outcome in spontaneous intracerebral hemorrhage: a machine learning approach by Anni Chen, Jiahui Wang, Qiaoying Huang, Chaoxiong Shen, Zhizhou Hu, Xiaohong Hu (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-13627042.txt.
Description
Anni Chen, Xiaohong Hu, and four co-authors test a blood index that may predict pneumonia after brain bleed. Their study, from twenty twenty-six, covers spontaneous bleeding inside the brain. Lung infection is a top complication of such strokes. The index blends counts of several immune cell types into one value.
Three hundred seventy-one patients form the cohort. Nine machine learning models were built and compared for two outcomes. One is the lung infection, and the other is poor function at ninety days. A high index tied strongly to both outcomes on its own. Adding it to the models lifted their accuracy. Charts that explain each prediction help doctors trust the output.
Catalog record
| CREATOR | Anni Chen, Jiahui Wang, Qiaoying Huang, Chaoxiong Shen, Zhizhou Hu, Xiaohong Hu |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 41 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |