Urology

Radiomics and Artificial Intelligence for Renal Mass Characterization.

Radiomics allows for high throughput extraction of quantitative data from images. This is an area of active research as groups try to capture and quantify imaging parameters and convert these into descriptive phenotypes of organs or tumors. Texture analysis is one radiomics tool that extracts information about heterogeneity within a given region of interest. This is used with or without associated...

Robot-Assisted Laparoscopic Partial Nephrectomy Conventional Laparoscopic Partial Nephrectomy: Functional and Surgical Outcomes of a Prospective Single Surgeon Randomized Study.

Laparoscopic partial nephrectomy (LPN) and robot-assisted partial nephrectomy (RAPN) are commonly used techniques for treating small renal masses. Regarding renal function (RF) preservation, no superiority of one technique over the other has yet been definitely demonstrated. To compare functional and surgical outcomes of LPN and RAPN. Between 2015 and 2019, we prospectively randomized 115 patie...

Semantic segmentation to identify bladder layers from H&E Images.

BACKGROUND: Identification of bladder layers is a necessary prerequisite to bladder cancer diagnosis and prognosis. We present a method of multi-class...

Identifying scenarios of benefit or harm from kidney transplantation during the COVID-19 pandemic: A stochastic simulation and machine learning study.

Clinical decision-making in kidney transplant (KT) during the coronavirus disease 2019 (COVID-19) pandemic is understandably a conundrum: both candida...

Robotic Versus Open Ureteroneocystostomy: Is There a Robotic Benefit?

We sought to compare the outcomes of patients who underwent an open robotic ureteroneocystostomy for ureteral obstruction. Retrospective review was...

Effect of Missing Data Imputation on Deep Learning Prediction Performance for Vesicoureteral Reflux and Recurrent Urinary Tract Infection Clinical Study.

Missing observations are always a challenging problem that we have to deal with in diseases that require follow-up. In hospital records for vesicouret...

Kidney segmentation from computed tomography images using deep neural network.

BACKGROUND: The precise segmentation of kidneys and kidney tumors can help medical specialists to diagnose diseases and improve treatment planning, wh...

UFO: A tool for unifying biomedical ontology-based semantic similarity calculation, enrichment analysis and visualization.

BACKGROUND: Biomedical ontologies have been growing quickly and proven to be useful in many biomedical applications. Important applications of those d...

The benefit of prehabilitation and enhanced recovery in robot-assisted radical prostatectomy and the promising future of these protocols in the field of urologic oncology.

Impact of indocyanine green-guided extended pelvic lymph node dissection during robot-assisted radical prostatectomy.

OBJECTIVES: To evaluate the effectiveness of indocyanine green-guided extended pelvic lymph node dissection during robot-assisted radical prostatectom...

Identification of glomerular lesions and intrinsic glomerular cell types in kidney diseases via deep learning.

Identification of glomerular lesions and structures is a key point for pathological diagnosis, treatment instructions, and prognosis evaluation in kid...

Benefits of robotic cystectomy compared with open cystectomy in an Enhanced Recovery After Surgery program: A propensity-matched analysis.

OBJECTIVES: To compare the perioperative and oncological outcomes between robot-assisted radical cystectomy with intracorporeal urinary diversion vers...

DoseGAN: a generative adversarial network for synthetic dose prediction using attention-gated discrimination and generation.

Deep learning algorithms have recently been developed that utilize patient anatomy and raw imaging information to predict radiation dose, as a means t...

Aptamer based proteomic pilot study reveals a urine signature indicative of pediatric urinary tract infections.

OBJECTIVE: Current urinary tract infection (UTI) diagnostic strategies that rely on leukocyte esterase have limited accuracy. We performed an aptamer-...

Machine Segmentation of Pelvic Anatomy in MRI-Assisted Radiosurgery (MARS) for Prostate Cancer Brachytherapy.

PURPOSE: To investigate machine segmentation of pelvic anatomy in magnetic resonance imaging (MRI)-assisted radiosurgery (MARS) for prostate cancer us...

Effect of different general anaesthetics on ventricular repolarisation in robot-assisted laparoscopic prostatectomy.

BACKGROUND: Ventricular repolarisation is affected differently by the types of anaesthetics used. This study aimed to compare the effect of different ...

Machine learning of diffraction image patterns for accurate classification of cells modeled with different nuclear sizes.

Measurement of nuclear-to-cytoplasm (N:C) ratios plays an important role in detection of atypical and tumor cells. Yet, current clinical methods rely ...

Machine learning prediction of stone-free success in patients with urinary stone after treatment of shock wave lithotripsy.

BACKGROUND: The aims of this study were to determine the predictive value of decision support analysis for the shock wave lithotripsy (SWL) success ra...

Machine learning for the identification of clinically significant prostate cancer on MRI: a meta-analysis.

OBJECTIVES: The aim of this study was to systematically review the literature and perform a meta-analysis of machine learning (ML) diagnostic accuracy...

Bioinformatics analysis of the genes involved in the extension of prostate cancer to adjacent lymph nodes by supervised and unsupervised machine learning methods: The role of SPAG1 and PLEKHF2.

The present study aimed to identify the genes associated with the involvement of adjunct lymph nodes of patients with prostate cancer (PCa) and to pro...