ArticleScientific reports2025
CT radiomics to assess severity of explosion-induced primary blast lung injury in goats.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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12 authors.
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Abstract
Previous studies on primary blast lung injury have mostly been small-sample simulation experiments, primarily relying on morphological identification and lacking imaging-based classification of severity. Herein, we have established a large-sample model of goats exposed to real natural field explosions and employed CT radiomics to assess the severity of lung injury. By extracting 1288 radiomics features and combining baseline data, baseline, radiomics, and comprehensive models were built. Results showed that the radiomics and comprehensive models outperformed the baseline model. Decision curve analysis indicated better clinical benefits with models incorporating rad-scores. A nomogram established with multiple factors demonstrated individualized predictive performance. The addition of CT radiomics features improved assessment accuracy and is expected to support clinical decision-making.
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