Purpose To develop and validate a machine learning multimodality model based on
preoperative MRI, surgical whole-slide imaging (WSI), and clinical variables for predicting …

Background We developed and validated an integrated radiomic-clinicopathologic
nomogram (RadClip) for post-surgical biochemical recurrence free survival (bRFS) and …

Background: To identify multiparametric magnetic resonance imaging (mp-MRI)-based
radiomics features as prognostic factors in patients with localized prostate cancer after …

Adjuvant radiotherapy after prostatectomy was recently challenged by early salvage
radiotherapy, which highlighted the need for biomarkers to improve risk stratification …

Objective To build a combined model that integrates clinical data, contrast-enhanced
ultrasound, and magnetic resonance perfusion-weighted imaging-based radiomics for …

Background Biochemical recurrence (BCR) affects a significant proportion of patients who
undergo robotic‐assisted laparoscopic prostatectomy (RALP). Purpose To evaluate the …

Background Radiomics or computer‐extracted texture features derived from MRI have been
shown to help quantitatively characterize prostate cancer (PCa). Radiomics have not been …

Simple Summary Existing research on predicting biochemical recurrence after prostate
surgery has been insufficient. Here, we aimed to predict biochemical recurrence after radical …

Background To investigate the predictive ability of high-throughput MRI with deep survival
networks for biochemical recurrence (BCR) of prostate cancer (PCa) after prostatectomy …

Background The detection of local recurrence for prostate cancer (PCa) patients following
radical prostatectomy (RP) is challenging and can influence the treatment plan. Our aim was …