Development and validation of a machine learning-driven framework for differentiating pediatric bronchopneumonia from lobar pneumonia: a multicenter investigation
Zihan Cai, Shoupeng Ding, Jinghua Gao · 2025
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Description
Zihan Cai, Shoupeng Ding, and Jinghua Gao build a computer tool to tell two kinds of lung infection apart in children, in work from twenty twenty-five. One kind spreads through small airways, while the other fills a whole lobe of the lung. Early sorting helps doctors pick the right care and skip needless steps.
The team used records from more than two thousand sick children at one hospital, plus a check set from elsewhere. Blood tests gave the clues, and three measures stood out as the best signs. A boosted tree model sorted the two kinds with high scores in all test sets. A simple chart form of the tool was also built for clinic use.
Catalog record
| CREATOR | Zihan Cai, Shoupeng Ding, Jinghua Gao |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 63 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |