RATIONALE AND OBJECTIVES
The clinical management of Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions remains controversial due to their equivocal likelihood of clinically significant prostate cancer (csPCa). This study aimed to develop and validate a prediction model for csPCa detection to assist in clini...
G. Gao, Ke-Xin Wang, Xiao-Ying Wang et al.· Academic Radiology· 0 citations
The deep learning-based AI model enables automated segmentation and detection of FLLs on NC-MRI, with acceptable performance across different lesion sizes, including benign and malignant lesions.
Duo-Duo Zhang, Ke Wang, Peng-Sheng Wu et al.· Abdominal Radiology· 0 citations
The developed model achieves high sensitivity and precise automated gallstone segmentation on CT images and achieves overall sensitivities of 97.2%, 97.5%, 95.2%, 89.2%, and 98.2% across the training, validation, internal test, hold-out, and AMOS datasets.