Comparing the performance of radiomics, nomograms, machine learning, and large language models in predicting 28-day mortality in severe community-acquired pneumonia patients

BackgroundSevere community-acquired pneumonia (SCAP) is a significant global health challenge due to its high mortality. Despite advances, early diagnosis and effective management remain critical. Tools like radiomics analyze imaging data for risk asse…

The role of CTGF and MFG-E8 in the prognosis assessment of SCAP: a study combining machine learning and nomogram analysis

BackgroundSevere Community-Acquired Pneumonia (SCAP) is a serious global health issue with high incidence and mortality rates. In recent years, the role of biomarkers such as Connective Tissue Growth Factor (CTGF) and Milk Fat Globule-Epidermal Growth …

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