Latest AI and machine learning research in urology for healthcare professionals.
This paper proposes an encoder-decoder architecture for kidney segmentation. A hyperparameter optimization process is implemented, including the development of a model architecture, selecting a windowing method and a loss function, and data augmentation. The model consists of EfficientNet-B5 as the encoder and a feature pyramid network as the decoder that yields the best performance with a Dice sc...
Radar systems can be used to perform human activity recognition in a privacy preserving manner. This can be achieved by using Deep Neural Networks, which are able to effectively process the complex radar data. Often these networks are large and do not scale well when processing a large amount of radar streams at once, for example when monitoring multiple rooms in a hospital. This work presents a f...
BACKGROUND: The gold standard treatment method for end-stage renal disease (ESRD) is renal transplantation (RT). RT can be done with open or minimally...
INTRODUCTION: We evaluated oncological outcomes of patients undergoing robot-assisted radical prostatectomy (RARP) for prostate cancer (PCa) and their...
DNA nanomachines with artificial intelligence have attracted great interest, which may open a new era of precision medicine. However, their in vivo be...
Artificial intelligence (AI) can extract visual information from histopathological slides and yield biological insight and clinical biomarkers. Whole ...
OBJECTIVE: The purpose of this study is to evaluate the ability of three metrics to monitor for a reduction in performance of a chronic kidney disease...
BACKGROUND: Although some robotic systems have been developed to improve conventional flexible ureteroscopy (FURS), a widely used intervention in urol...
To analyze operating room (OR) efficiency by evaluating fixed OR times for three common urologic robot-assisted procedures. Over a 24-month period, ...
Accurate diagnosis and grading of needle biopsies are crucial for prostate cancer management. A uropathologist-level artificial intelligence (AI) syst...
The decision-making of how to treat urinary infection stones was complicated by the difficulty in preoperative diagnosis of these stones. Hence, we d...
OBJECTIVES: The most common complications after radical prostatectomy (RP) are erectile dysfunction (ED) and urinary incontinence (UI). After RP, pati...
PURPOSE: To evaluate the safety, efficacy, and clinical impact of preoperative cone-beam computed tomography (CT)-guided selective embolization of end...
To determine the stone-free rates (SFR) with robot-assisted mini-endoscopic combined intrarenal surgery (mini-ECIRS) and evaluate the impact of intra...
OBJECTIVES: The aim of this study was to estimate the prospective utility of a previously retrospectively validated convolutional neural network (CNN)...
BACKGROUND: Transplant nephropathology is a highly specialized field of pathology comprising both the evaluation of organ donor biopsy for organ alloc...
Recently, cytoreductive prostatectomy for metastatic prostate cancer (mPCa) has been associated with improved oncological outcomes. This study was aim...
Deep learning consistently demonstrates high performance in classifying and segmenting medical images like CT, PET, and MRI. However, compared to thes...
PURPOSE: The purpose of this study was to investigate the effect of a surgically constructed bilateral peritoneal flap (PIF) as an adjunct to robot-as...
OBJECTIVE: The feasibility of tracer production of technetium (Tc)-prostate-specific membrane antigen (PSMA)-I&S sterile cold kit, imaging with single...