BACKGROUNDS: Delayed cerebral ischemia (DCI) is a significant complication following aneurysmal subarachnoid hemorrhage (aSAH), leading to poor prognosis and high mortality. This study developed a non-contrast CT (NCCT)-based radiomics nomogram for e...
BACKGROUND: Rheumatoid arthritis (RA) is an autoimmune inflammatory disease. The mechanism by which telomeres are involved in the development of RA remains unclear. This study aimed to investigate the relationship between RA and telomeres.
BACKGROUND: Immune Checkpoint Inhibitor-related Pneumonitis (CIP) exhibits high morbidity and mortality rates in the real world, often coexisting with pneumonia, particularly after immunochemotherapy. We aimed to develop and validate a non-invasive n...
Hospital-acquired pneumonia (HAP) is prevalent in the neuro-intensive care unit (NICU), significantly increasing susceptibility to infections with multidrug-resistant organisms (MDROs), which result in high mortality rates and substantial healthcare ...
Background: Septic shock-associated acute kidney injury (SS-AKI) is a severe complication with high mortality. This study aimed to investigate the risk factors associated with AKI in patients with septic shock and establish a nomogram to predict its ...
PURPOSE: This study is aimed to develop and validate a machine learning model, which combined radiomics and clinical characteristics to predicting the definitive chemoradiotherapy (dCRT) treatment response in esophageal squamous cell carcinoma (ESCC)...
BACKGROUND: To develop and validate deep learning (DL) and traditional clinical-metabolic (CM) models based on 18 F-FDG PET/CT images for noninvasively predicting high-grade patterns (HGPs) of invasive lung adenocarcinoma (LUAD).
PURPOSE: To establish and validate a model based on deep learning (DL), integrating radiomic features with relevant clinical features to generate nomogram, for predicting preoperative serosal invasion in gastric cancer (GC).
OBJECTIVE: This study develops and validates a machine learning model using peritoneal cytology to predict distant metastasis in uterine carcinosarcoma, aiding clinical decision-making.
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