Urology

Prospective Nonrandomized Comparison Between Open and Robot-Assisted Kidney Transplantation: Analysis of Midterm Functional Outcomes.

To compare short- and midterm outcomes of the first 55 patients undergoing robot-assisted kidney transplant (RAKT) with patients undergoing open kidney transplant (OKT) during the same period in a tertiary care hospital. Data of all end-stage renal disease patients undergoing renal transplant were prospectively maintained. All graft kidneys were harvested laparoscopically. Both RAKT and OKT were...

Deep adaptive registration of multi-modal prostate images.

Artificial intelligence, especially the deep learning paradigm, has posed a considerable impact on cancer imaging and interpretation. For instance, fusing transrectal ultrasound (TRUS) and magnetic resonance (MR) images to guide prostate cancer biopsy can significantly improve the diagnosis. However, multi-modal image registration is still challenging, even with the latest deep learning technology...

Prediction of the development of acute kidney injury following cardiac surgery by machine learning.

BACKGROUND: Cardiac surgery-associated acute kidney injury (CSA-AKI) is a major complication that results in increased morbidity and mortality after c...

Prostate cancer trajectory-map: clinical decision support system for prognosis management of radical prostatectomy.

PURPOSE: Prostate cancer has a low mortality rate and requires persistent treatment; however, treatment decisions are challenging. Because prostate ca...

Deep learning using preoperative magnetic resonance imaging information to predict early recovery of urinary continence after robot-assisted radical prostatectomy.

OBJECTIVES: To investigate whether a deep learning model from magnetic resonance imaging information is an accurate method to predict the risk of urin...

Re-establishing the Role of Robot-assisted Radical Cystectomy After the 2020 EAU Muscle-invasive and Metastatic Bladder Cancer Guideline Panel Recommendations.

The EAU guidelines panel on muscle-invasive and metastatic bladder cancer (MIBC) recently recommended open radical cystectomy (ORC) as the best surgic...

Identifying prostate cancer and its clinical risk in asymptomatic men using machine learning of high dimensional peripheral blood flow cytometric natural killer cell subset phenotyping data.

We demonstrate that prostate cancer can be identified by flow cytometric profiling of blood immune cell subsets. Herein, we profiled natural killer (N...

Clinical impact of psoas muscle volume on the development of inguinal hernia after robot-assisted radical prostatectomy.

BACKGROUND: Sarcopenia, a syndrome characterized by the loss of skeletal muscle mass, has attracted attention in the field of oncology, as it reflects...

Cone-beam CT-derived relative stopping power map generation via deep learning for proton radiotherapy.

PURPOSE: In intensity-modulated proton therapy (IMPT), protons are used to deliver highly conformal dose distributions, targeting tumors, and sparing ...

A deep learning framework for prostate localization in cone beam CT-guided radiotherapy.

PURPOSE: To develop a deep learning-based model for prostate planning target volume (PTV) localization on cone beam computed tomography (CBCT) to impr...

Early Prediction of Acute Kidney Injury in the Emergency Department With Machine-Learning Methods Applied to Electronic Health Record Data.

STUDY OBJECTIVE: Acute kidney injury occurs commonly and is a leading cause of prolonged hospitalization, development and progression of chronic kidne...

Test-retest repeatability of a deep learning architecture in detecting and segmenting clinically significant prostate cancer on apparent diffusion coefficient (ADC) maps.

OBJECTIVES: To evaluate short-term test-retest repeatability of a deep learning architecture (U-Net) in slice- and lesion-level detection and segmenta...

: deep learning-based radiomics for the time-to-event outcome prediction in lung cancer.

Hand-crafted radiomics has been used for developing models in order to predict time-to-event clinical outcomes in patients with lung cancer. Hand-craf...

MAGPEL: an autoMated pipeline for inferring vAriant-driven Gene PanEls from the full-length biomedical literature.

In spite of the efforts in developing and maintaining accurate variant databases, a large number of disease-associated variants are still hidden in th...

Development and Validation of a Deep-learning Model to Assist With Renal Cell Carcinoma Histopathologic Interpretation.

OBJECTIVE: To develop and test the ability of a convolutional neural network (CNN) to accurately identify the presence of renal cell carcinoma (RCC) o...

A deep learning method for real-time intraoperative US image segmentation in prostate brachytherapy.

PURPOSE: This paper addresses the detection of the clinical target volume (CTV) in transrectal ultrasound (TRUS) image-guided intraoperative for perma...

Reply to Francesco Montorsi, Marco Bandini, Alberto Briganti, et al. Re-establishing the Role of Robot-assisted Radical Cystectomy After the 2020 EAU Muscle-invasive and Metastatic Bladder Cancer Guideline Panel Recommendations. Eur Urol 2020;78:489-91: Can Open and Robotic Radical Cystectomy be Considered Equally Effective in 2020?

Structure equation model and neural network analyses to predict coronary artery lesions in Kawasaki disease: a single-centre retrospective study.

A new method to predict coronary artery lesions (CALs) in Kawasaki disease (KD) was developed using a mean structure equation model (SEM) and neural n...

Comparison of machine learning algorithms to predict clinically significant prostate cancer of the peripheral zone with multiparametric MRI using clinical assessment categories and radiomic features.

OBJECTIVES: To analyze the performance of radiological assessment categories and quantitative computational analysis of apparent diffusion coefficient...

Deep learning applications in automatic needle segmentation in ultrasound-guided prostate brachytherapy.

PURPOSE: High-Dose-Rate (HDR) brachytherapy is one of the most effective ways to treat the prostate cancer, which is the second most common cancer in ...