Urology

Surgery's Rosetta Stone: Natural language processing to predict discharge and readmission after general surgery.

BACKGROUND: This study aimed to examine the accuracy with which multiple natural language processing artificial intelligence models could predict discharge and readmissions after general surgery.

Physics-informed neural network for fast prediction of temperature distributions in cancerous breasts as a potential efficient portable AI-based diagnostic tool.

This work presents the development of a novel Physics-Informed Neural Network (PINN) method for fast forward simulation of heat transfer through cancerous breast models. The proposed PINN method combines deep learning and physical principles to predict the temperature distributions in breast tissues and identify potential abnormal regions indicating the presence of tumors. The PINN model is normal...

A deep learning image analysis method for renal perfusion estimation in pseudo-continuous arterial spin labelling MRI.

Accurate segmentation of renal tissues is an essential step for renal perfusion estimation and postoperative assessment of the allograft. Images are u...

Development of an automated estimation of foot process width using deep learning in kidney biopsies from patients with Fabry, minimal change, and diabetic kidney diseases.

Podocyte injury plays a key role in pathogenesis of many kidney diseases with increased podocyte foot process width (FPW), an important measure of pod...

Long term efficacy of prosthetic inguinal herniorrhaphy concomitant with robot-assisted laparoscopic radical prostatectomy.

PURPOSE: Patients who undergo robot-assisted laparoscopic radical prostatectomy (RARP) may present concurrent or secondary inguinal hernia (IH). Surgi...

Advantages of enhanced recovery after surgery program in robot-assisted radical cystectomy.

Radical cystectomy is a gold-standard treatment for muscle-invasive bladder cancer. We recently introduced robot-assisted radical cystectomy (RARC) wi...

Deep learning-enabled realistic virtual histology with ultraviolet photoacoustic remote sensing microscopy.

The goal of oncologic surgeries is complete tumor resection, yet positive margins are frequently found postoperatively using gold standard H&E-stained...

Optimal interval for delayed retrieval surgery with reciprocating morcellators after enucleation of giant prostatic hyperplasia in holmium laser enucleation of the prostate.

OBJECTIVE: The aim of this research was to evaluate the efficiency of reciprocating morcellation for removing giant benign prostatic hyperplasia durin...

Variations in predictors for urinary continence recovery at different time periods following robot-assisted radical prostatectomy.

INTRODUCTION: Urinary dysfunctions are common sequelae following prostatectomy. This study aimed to discover factors that can predict urinary continen...

Is Urethral Catheterization Necessary in Retzius-sparing Robot-assisted Radical Prostatectomy?

OBJECTIVE: To analyze whether urethral catheter (UC)-free anastomosis during Retzius-sparing radical prostatectomy (RP) results in worsening immediate...

A new architecture combining convolutional and transformer-based networks for automatic 3D multi-organ segmentation on CT images.

PURPOSE: Deep learning-based networks have become increasingly popular in the field of medical image segmentation. The purpose of this research was to...

Comparing pentafecta outcomes between nerve sparing and non nerve sparing robot-assisted radical prostatectomy in a propensity score-matched study.

Pentafecta (continence, potency, cancer control, free surgical margins, and no complications) is an important outcome of prostatectomy. Our objective ...

Comparison of effectiveness and safety of Da Vinci robot's "3 + 1" and "4 + 1" modes of treatment for colorectal cancer.

To compare the effectiveness of the Da Vinci Surgical Robot System (DSRS) "3 + 1" and "4 + 1" models for colorectal cancer (CRC). A total of 107 patie...

Application of serum SERS technology combined with deep learning algorithm in the rapid diagnosis of immune diseases and chronic kidney disease.

Surface-enhanced Raman spectroscopy (SERS), as a rapid, non-invasive and reliable spectroscopic detection technique, has promising applications in dis...

Quantifying acute kidney injury in an Ischaemia-Reperfusion Injury mouse model using deep-learning-based semantic segmentation in histology.

This study focuses on ischaemia-reperfusion injury (IRI) in kidneys, a cause of acute kidney injury (AKI) and end-stage kidney disease (ESKD). Traditi...

Robot-assisted versus open radical prostatectomy: a systematic review and meta-analysis of prospective studies.

The study aims to synthesize all available prospective comparative studies and reports the latest systematic analysis and updated evidence comparing r...

Research on texture images and radiomics in urology: a review of urological MR imaging applications.

PURPOSE OF REVIEW: Tumor volume and heterogenicity are associated with diagnosis and prognosis of urological cancers, and assessed by conventional ima...

CT-based deep learning radiomics nomogram for the prediction of pathological grade in bladder cancer: a multicenter study.

BACKGROUND: To construct and assess a computed tomography (CT)-based deep learning radiomics nomogram (DLRN) for predicting the pathological grade of ...

Dose Optimization Using a Deep Learning Tool in Various CT Protocols for Urolithiasis: A Physical Human Phantom Study.

We attempted to determine the optimal radiation dose to maintain image quality using a deep learning application in a physical human phantom. Three ...

Artificial Intelligence in Pediatric Urology.

Application of artificial intelligence (AI) is one of the hottest topics in medicine. Unlike traditional methods that rely heavily on statistical assu...