Urology

Intraoperative assessment of surgical margins during radical prostatectomy: advances and challenges.

PURPOSE OF REVIEW: Detection of positive surgical margins during radical prostatectomy is critical to minimizing the risk of prostate cancer recurrence. This review deals with established methods, recent advances in real-time intraoperative technologies, and future directions in margin assessment. RECENT FINDINGS: This review examines traditional methods, real-time technologies, and prospects in i...

Self-Supervised Noise Adaptive MRI Denoising via Repetition to Repetition (Rep2Rep) Learning.

PURPOSE: This work proposes a novel self-supervised noise-adaptive image denoising framework, called Repetition to Repetition (Rep2Rep) learning, for low-field ( < $$ < $$ 1T) MRI applications. METHODS: Rep2Rep learning extends the Noise2Noise framework by training a neural network on two repeated MRI acquisitions, using one repetition as input and another as target, without requiring ground-tru...

Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.

Chronic kidney disease (CKD) represents a major and expanding global health challenge, with prevalence rising due to aging populations, diabetes, hype...

Integrative Machine Learning Model Leveraging DCE-MRI and PSA Values for Advanced Risk Stratification in Prostate Cancer.

PURPOSE: Accurate grading of prostate cancer is critical for treatment strategies and risk stratification. This study aims to develop a machine learni...

Responsible Use of Artificial Intelligence to Improve Kidney Care: A Statement from the American Society of Nephrology.

Artificial intelligence (AI) is rapidly transforming the delivery of kidney care through predictive analytics, machine learning, deep learning, and ge...

The application of machine learning in the evaluation of urinary tract infections incidence in patients in a Nursing and Treatment Facility.

BACKGROUND: Urinary tract infection (UTI) is a serious problem in the healthcare system. It is caused by bacteria from the gastrointestinal tract. The...

Renal Cell Carcinoma subtyping: Learning from multi-resolution localization.

BACKGROUND AND OBJECTIVE: Renal Cell Carcinoma (RCC) is often diagnosed at advanced stages, limiting treatment options. Since prognosis depends on tum...

Evaluation of an artificial intelligence model based on multiparametric transrectal ultrasound for localizing clinically significant prostate cancer by simulation of targeted biopsies.

INTRODUCTION AND OBJECTIVES: An AI model that performs well during training does not guarantee similar performance in clinical practice and should be ...

Combination of a modified dietary tool and spot urine collection: an improved method for daily sodium intake estimation.

PURPOSE: Recently, an improved food frequency questionnaire focused on assessing daily sodium (Na) intake (Food Frequency Questionnaire [FFQ]-Na: 73 q...

Machine Learning-Based Analysis of UF-5000 Scattergrams Improves the Identification of Urinary Dysmorphic Red Blood Cells.

BACKGROUND: Identifying dysmorphic red blood cells (RBCs) is critical for diagnosing glomerular diseases, as distinguishing glomerular from non-glomer...

Automatically Measuring Kidney, Liver, and Cyst Volumes in Autosomal Dominant Polycystic Kidney Disease.

KEY POINTS: TraceOrg is a web-based tool that automatically labels kidney, liver, and cysts, reporting volumes and Mayo Imaging Classification. Extern...

Development and Deployment of a Machine Learning Model to Triage the Use of Prostate MRI (ProMT-ML) in Patients With Suspected Prostate Cancer.

BACKGROUND: Access to prostate MRI remains limited due to resource constraints and the need for expert interpretation. PURPOSE: To develop machine lea...

Towards Precision Oncology: A New Predictive Machine Learning Model for Early Progression to Castration Resistant Prostate Cancer.

BACKGROUND AND OBJECTIVE: Metastatic castration-resistant prostate cancer (mCRPC) is an aggressive, lethal state of prostate cancer, for which early p...

Artificial intelligence-based segmentation of small renal masses: a multi-center, multi-scanner, multi-sequence study.

OBJECTIVES: This study aims to develop an artificial intelligence (AI)-based automated segmentation method for small renal masses (SRMs) using multi-c...

Advanced artificial intelligence combined with SERS platforms for diagnosis and therapeutic effects of cancer in clinical applications.

Surface-Enhanced Raman Spectroscopy (SERS) has become a valuable way to detect small amounts of molecules due to its high sensitivity. Nonetheless, ap...

Comparison of glass-based and whole-slide image-based grade assignment for clear-cell and papillary renal cell carcinoma: a multi-cohort, international reproducibility study.

BACKGROUND AND AIMS: Histological grading of renal cell carcinoma (RCC) is an important part of diagnostic evaluation. Reproducibility of RCC grading ...

Impact of hypotension prediction index-guided management on intraoperative hypotension and postoperative outcomes in abdominal surgery: A meta-analysis of randomized controlled trials.

BACKGROUND: The Hypotension Prediction Index (HPI) is a machine-learning algorithm designed to predict hypotension. by maintaining mean arterial press...

An Interpretable Machine Learning Model for Early Multitemporal Prediction of Onset of Acute Kidney Injury in Intensive Care Unit Patients with Severe Trauma.

Background: Acute Kidney Injury (AKI), a leading organ failure cause in critical patients, demands early high-risk identification to enhance outcomes....

Correction to: Kidney Week 2025 Abstract Artificial Intelligence in Autosomal Dominant Polycystic Kidney Disease: Transforming Diagnosis, Risk Stratification, and Therapeutic Interventions SA-PO0555.

Xception Convolutional Deep Maxout Network for Enhanced Breast Cancer Classification Using Histopathological Images.

Globally, breast cancer represents the leading cancer type, with millions of women impacted annually. The success of breast cancer treatment relies he...