Li Mao

TL;DR: The proposed DL model based on CT images exhibited relatively good prediction ability of muscle-invasive status ofBCa preoperatively, which may improve individual treatment of BCa.

TL;DR: This study investigated the feasibility of a computed tomography (CT)-based radiomics prediction model to evaluate muscle invasive status in bladder cancer and found that it can evaluate muscle invasiveness of bladder cancer before surgery with a good diagnostic performance.

TL;DR: M 3 Net as mentioned in this paper integrates multi-scale multi-view information for multi-phase pancreas segmentation, where cross-phase interactive connections bridging the two branches are introduced to interleave and integrate dual-phase complementary visual information.

TL;DR: In this article , the authors compared the radiomics machine learning (ML) models based on non-contrast enhanced computed tomography (NECT) and clinical features for predicting the simplified risk categorization of thymic epithelial tumors (TETs).