ObjectiveThis study aims to develop and externally validate a contrast-enhanced magnetic resonance imaging (CE-MRI) radiomics-based model for preoperative differentiation between fat-poor angiomyolipo
Data are presented as median (range).HCC: hepatocellular carcinoma, HCA: hepatocellular adenoma, FNH: focal nodular hyperplasia, GP73: Golgi Protein 73, AFP: alpha-fetoprotein.
This dataset is designed to support the development of artificial intelligence models for the differential diagnosis of liver tumors. It comprises contrast-enhanced CT scans of NIFTI format from five
ObjectivesTo establish a nomogram based on preoperative laboratory study variables using least absolute shrinkage and selection operator (LASSO) regression for differentiating combined hepatocellular
Medical professionals are well aware that imaging techniques are not infallible in accurately diagnosing cancer or staging patients with histologically confirmed cancer. Pathologists often emerge as g