Based on a radiomics-clinical nomogram to predict the therapeutic effect of pulmonary cryptococcosis pneumonia
Yan-li Zhang, Chao Ran, Wei Li · 2026
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Description
Yan-li Zhang, Chao Ran, and Wei Li build a prediction chart in 2026. The chart forecasts treatment effect in a fungal lung infection. The infection is pulmonary cryptococcosis. Its CT look overlaps with other diseases. The tool mines texture patterns from scans. The eye cannot quantify those patterns alone.
Records covered 255 patients at two centres. Sets were split into training and validation groups. One set came from a second centre for external checks. A support vector machine performed best among the models. It used selected scan features as inputs. Adding clinical variables made a combined nomogram. That chart matched the scan-only model. It clearly beat a clinical-only model.
Catalog record
| CREATOR | Yan-li Zhang, Chao Ran, Wei Li |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 32130 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |