PURPOSE: Radical cystectomy (RC) with urinary diversion (UD) is still considered a complex surgery associated with significant morbidity. Open RC (ORC) remains the reference option of treatment, even if adoption of robot-assisted RC (RARC) is rapidly...
Technological advances, in particular the development of high-throughput sequencing, have led to the emergence of a new generation of molecular biomarkers for tumors. These new tools have profoundly changed therapeutic management in oncology, with in...
BACKGROUND: To evaluate long-term oncological and renal function outcomes in patients treated with robot-assisted partial nephrectomy (RAPN) for renal cell carcinoma (RCC).
Uretero-enteric anastomotic strictures (UES) after robot-assisted radical cystectomy (RARC) represent the main cause of post-operative renal dysfunction. The gold standard for treatment of UES is open uretero-ileal reimplantation (UIR), which is ofte...
BACKGROUND: With the development of minimally invasive surgery technology, patients with bladder cancer are increasingly receiving laparoscopic radical cystectomy (LRC) or robotic-assisted radical cystectomy (RARC) treatment. The main purpose of this...
BACKGROUND: Accurate response evaluation is necessary to select complete responders (CRs) for a watch-and-wait approach. Deep learning may aid in this process, but so far has never been evaluated for this purpose. The aim was to evaluate the accuracy...
OBJECTIVES: To evaluate the performance of a deep learning radiomic nomogram (DLRN) model at predicting tumor relapse in patients with soft tissue sarcomas (STS) who underwent surgical resection.
AJR. American journal of roentgenology
Aug 11, 2021
Postoperative mammograms present interpretive challenges due to postoperative distortion and hematomas. The application of digital breast tomosyn-thesis (DBT) and artificial intelligence-based computer-aided detection (AI-CAD) after breast-conservin...
Individualized patient profiling is instrumental for personalized management in hepatocellular carcinoma (HCC). This study built a model based on bidirectional deep neural networks (BiDNNs), an unsupervised machine-learning approach, to integrate mu...
For a patient affected by breast cancer, after tumor removal, it is necessary to decide which adjuvant therapy is able to prevent tumor relapse and formation of metastases. A prediction of the outcome of adjuvant therapy tailored for the patient is h...