Association of radiogenomic characteristics and gene expression profiles in hepatocellular carcinoma Overall design: Total 81 HCCs with PET information were sequenced to identify gene expressions. **R

NIAID Data Ecosystem70

AusCAT Simulation Tabular Data

癌症放射组学

肿瘤影像分析

This data is part of the NCLC Radiomics dataset provided by The Cancer Imaging Archive (TCIA) and is released under the Creative Commons Attribution 3.0 Unported License. CAUTION: This data is

NIAID Data Ecosystem50

DataSheet_5_Radiogenomics analysis reveals the associations of dynamic contrast-enhanced–MRI features with gene expression characteristics, PAM50 subtypes, and prognosis of breast cancer.xlsx

癌症放射组学

影像特征预后预测

BackgroundTo investigate reliable associations between dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) features and gene expression characteristics in breast cancer (BC) and to develop

NIAID Data Ecosystem80

Additional file 4 of Multi-machine learning model based on radiomics features to predict prognosis of muscle-invasive bladder cancer

肿瘤影像预后预测

癌症放射组学

Supplementary Material 4

NIAID Data Ecosystem50