Radiomics integrated with artificial intelligence offers a pioneering approach to urologic
oncology, ushering in an era of enhanced diagnostic precision and reduced invasiveness …

Background To construct and assess a computed tomography (CT)-based deep learning
radiomics nomogram (DLRN) for predicting the pathological grade of bladder cancer (BCa) …

Objective To establish a model for predicting lymph node metastasis in bladder cancer
(BCa) patients. Methods We retroactively enrolled 239 patients who underwent three-phase …

Objectives Open-access cancer imaging datasets have become integral for evaluating novel
AI approaches in radiology. However, their use in quantitative analysis with radiomics …

Objective The purpose of this study was to construct a 3D and 2D contrast-enhanced
computed tomography (CECT) radiomics model to predict CGB3 levels and assess its …

Background: Muscle invasive bladder cancer (MIBC) has a poor prognosis even after radical
cystectomy (RC). Postoperative survival stratification based on radiomics and deep learning …

Purpose To establish a prognostic model to estimate progression-free survival (PFS)
probability in bladder cancer (BCa) patients undergoing partial cystectomy. Material and …

Objectives To assess the predictive value of intratumoral and peritumoral radiomics based
on Dual-energy CT urography (DECTU) multi-images for preoperatively predicting the …

泌尿系统肿瘤的发病率正逐年提高, 严重威胁着我国人民的健康. 准确评估疾病的预后对于泌尿
系统肿瘤患者至关重要. 影像组学是在CT, MRI 等传统影像检查的基础上 …

Purpose To construct a radiomics-clinical nomogram model for predicting the risk of local
and metastatic recurrence within 3 years after radical cystectomy (RC) of bladder cancer …