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Single-cell and spatial multi-omics combined with machine learning to unravel the heterogeneity of cholangiocarcinoma and the WFDC3-mediated prognostic regulatory mechanisms
Intrahepatic cholangiocarcinoma (ICC) exhibits substantial cellular heterogeneity and a complex tumor microenvironment (TME), contributing to poor clinical outcomes. Effective prognostic biomarkers and a deeper understanding of the cellular ecosystems associated with high-risk disease remain urgently needed....
A CT-based deep learning model for the automated risk stratification of refractory Mycoplasma pneumoniae pneumonia in children.
The trans-DLF provides a streamlined and efficient approach to RMPP risk assessment in children who have already undergone clinically indicated chest CT and may support timely, evidence-based decision-making without additional tests.