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Comparing the performance of radiomics, nomograms, machine learning, and large language models in predicting 28-day mortality in severe community-acquired pneumonia patients
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Zitationen
6
Autoren
2026
Jahr
Abstract
This study demonstrates the effectiveness of radiomics, machine learning, and LLMs to predict SCAP outcomes. Models like XGBoost achieved superior accuracy, while SHAP analysis improved interpretability. These advancements highlight the potential for enhanced SCAP prognosis and personalized care strategies.
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