Urology

Latest AI and machine learning research in urology for healthcare professionals.

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Electrocardiography-based Artificial Intelligence Algorithms Aid in Prediction of Long-term Mortality After Kidney Transplantation.

BACKGROUND: Predicting long-term mortality postkidney transplantation (KT) using baseline clinical d...

Using neural networks to autonomously assess adequacy in intraoperative cholangiograms.

BACKGROUND: Intraoperative cholangiography (IOC) is a contrast-enhanced X-ray acquired during laparo...

Bioinspired multiscale adaptive suction on complex dry surfaces enhanced by regulated water secretion.

Suction is a highly evolved biological adhesion strategy for soft-body organisms to achieve strong g...

Development of risk-score model in patients with negative surgical margin after robot-assisted radical prostatectomy.

A total of 739 patients underwent RARP as initial treatment for PCa from November 2011 to October 20...

The ERUS course on robot-assisted kidney transplantation.

PURPOSE: Robot-assisted kidney transplantation (RAKT) is being increasingly performed at selected re...

Extended pelvic lymph node dissection in robot-assisted radical prostatectomy is an independent risk factor for major complications.

The aim of this study is to evaluate the major postoperative complication rate after robot-assisted ...

Deceased-Donor Kidney Transplant Outcome Prediction Using Artificial Intelligence to Aid Decision-Making in Kidney Allocation.

In kidney transplantation, pairing recipients with the highest longevity with low-risk allografts to...

Deep learning-based glomerulus detection and classification with generative morphology augmentation in renal pathology images.

Glomerulus morphology on renal pathology images provides valuable diagnosis and outcome prediction i...

Calculated Medicine: Seven Decades of Accelerating Growth.

The field of Calculated Medicine has grown substantially over the last 7 decades. Comprised of objec...

Machine learning in risk prediction of continuous renal replacement therapy after coronary artery bypass grafting surgery in patients.

OBJECTIVES: This study aimed to develop machine learning models for risk prediction of continuous re...

Model-agnostic explanations for survival prediction models.

Advanced machine learning methods capable of capturing complex and nonlinear relationships can be us...

Machine Learning-Assistant Colorimetric Sensor Arrays for Intelligent and Rapid Diagnosis of Urinary Tract Infection.

Urinary tract infections (UTIs), which can lead to pyelonephritis, urosepsis, and even death, are am...

Minimally invasive cytoreductive radical prostatectomy, exploring the safety and feasibility of a single-port or multi-port robotic platform.

BACKGROUND: Consolidative resection or cytoreductive radical prostatectomy (CRP) may benefit men wit...

Machine learning-based analysis of Ga-PSMA-11 PET/CT images for estimation of prostate tumor grade.

Early diagnosis of prostate cancer, the most common malignancy in men, can improve patient outcomes....

Comparison of model-based versus deep learning-based image reconstruction for thin-slice T2-weighted spin-echo prostate MRI.

PURPOSE: To compare a previous model-based image reconstruction (MBIR) with a newly developed deep l...

Development of Machine Learning Algorithm to Predict the Risk of Incontinence After Robot-Assisted Radical Prostatectomy.

Predicting postoperative incontinence beforehand is crucial for intensified and personalized rehabi...

Automated prostate gland segmentation in challenging clinical cases: comparison of three artificial intelligence methods.

OBJECTIVE: Automated methods for prostate segmentation on MRI are typically developed under ideal sc...

Extended pelvic lymph node dissection during robotic prostatectomy: antegrade versus retrograde technique.

BACKGROUND: Robot-assisted radical prostatectomy (RARP) with extended lymphadenectomy (ePLND) is the...

DiagSet: a dataset for prostate cancer histopathological image classification.

Cancer diseases constitute one of the most significant societal challenges. In this paper, we introd...

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