Urology

Letter to the editor for the article "A machine learning approach using stone volume to predict stone-free status at ureteroscopy".

Multiparametric MRI-Based Deep Learning Radiomics Model for Assessing 5-Year Recurrence Risk in Non-Muscle Invasive Bladder Cancer.

BACKGROUND: Accurately assessing 5-year recurrence rates is crucial for managing non-muscle-invasive...

Artificial Intelligence-Based Classification of CT Images Using a Hybrid SpinalZFNet.

The kidney is an abdominal organ in the human body that supports filtering excess water and waste fr...

Robotic MR-guided high dose rate brachytherapy needle implantation in the prostate (ROBiNSon)-a proof-of-concept study.

A robotic needle implant device for MR-guided high-dose-rate (HDR) prostate brachytherapy was develo...

is a novel marker for bladder cancer prognosis: evidence based on experimental studies, machine learning and single-cell sequencing.

BACKGROUND: Bladder cancer, a highly fatal disease, poses a significant threat to patients. Position...

Automated Bio-AFM Generation of Large Mechanome Data Set and Their Analysis by Machine Learning to Classify Cancerous Cell Lines.

Mechanobiological measurements have the potential to discriminate healthy cells from pathological ce...

Fast prediction of personalized abdominal organ doses from CT examinations by radiomics feature-based machine learning models.

The X-rays emitted during CT scans can increase solid cancer risks by damaging DNA, with the risk ti...

Construction and evaluation of a mortality prediction model for patients with acute kidney injury undergoing continuous renal replacement therapy based on machine learning algorithms.

BACKGROUND: To construct and evaluate a predictive model for in-hospital mortality among critically ...

Commentary on Machine Learning to Predict Prostate Artery Embolization Outcomes? Patient Selection for Prostatic Artery Embolization: Why it Matters.

Applying 12 machine learning algorithms and Non-negative Matrix Factorization for robust prediction of lupus nephritis.

Lupus nephritis (LN) is a challenging condition with limited diagnostic and treatment options. In th...

Predicting graft survival in paediatric kidney transplant recipients using machine learning.

BACKGROUND: Identification of factors that affect graft survival in kidney transplantation can incre...

Integrated structural proteomics and machine learning-guided mapping of a highly protective precision vaccine against mycoplasma pulmonis.

Mycoplasma pulmonis (M. pulmonis) is an emerging respiratory infection commonly linked to prostate c...

The application of blood flow sound contrastive learning to predict arteriovenous graft stenosis of patients with hemodialysis.

End-stage kidney disease (ESKD) presents a significant public health challenge, with hemodialysis (H...

Machine Learning-based Nomograms for Predicting Clinical Stages of Initial Prostate Cancer: A Multicenter Retrospective Study.

OBJECTIVE: To construct and externally validate machine learning-based nomograms for predicting prog...

Prediction of non-muscle invasive bladder cancer recurrence using deep learning of pathology image.

We aimed to build a deep learning-based pathomics model to predict the early recurrence of non-muscl...

Patient perspectives on the use of artificial intelligence in prostate cancer diagnosis on MRI.

OBJECTIVES: This study investigated patients' acceptance of artificial intelligence (AI) for diagnos...

Development of deep learning-based novel auto-segmentation for the prostatic urethra on planning CT images for prostate cancer radiotherapy.

Urinary toxicities are one of the serious complications of radiotherapy for prostate cancer, and dos...

Generative Artificial Intelligence Platform for Automating Social Media Posts From Urology Journal Articles: A Cross-Sectional Study and Randomized Assessment.

PURPOSE: This cross-sectional study assessed a generative artificial intelligence platform to automa...

The influence of mental calculations on brain regions and heart rates.

Performing mathematical calculations is a cognitive activity that can affect biological signals. Thi...

Self-normalization for a 1 mmresolution clinical PET system using deep learning.

This work proposes, for the first time, an image-based end-to-end self-normalization framework for p...

Development and validation of a machine learning-based, point-of-care risk calculator for post-ERCP pancreatitis and prophylaxis selection.

BACKGROUND AND AIMS: A robust model of post-ERCP pancreatitis (PEP) risk is not currently available....