Urology

Applicability of mitotic figure counting by deep learning: a development and pan-cancer validation study.

Mitotic figure counting is an established measure of cell proliferation that is included in grading systems. We developed a deep learning method for mitotic figure counting and evaluated its prognostic impact in multiple external validation datasets. The deep learning method was trained in whole slide images of tissue sections stained with haematoxylin and eosin from a publicly available breast ca...

Beyond sensitivity: artificial intelligence and micro-ultrasonography in prostate cancer detection.

A Comprehensive Approach to Days' Supply Estimation in a Real-World Prescription Database: Algorithm Development and Validation Study.

BACKGROUND: For accurate medication usage statistics and medication adherence calculations, we need to have an accurate days' supply (DS) for each pre...

A two-stage deep learning framework for kidney disease detection using modified specular-free imaging and EfficientNetB2.

Kidney diseases represent a substantial public health concern, with their incidence increasing markedly over the past decade. Addressing this challeng...

Integrative transcriptomic and machine learning analysis identifies PYCARD and IFI30 as immune-lysosomal biomarkers of ANCA-associated glomerulonephritis.

OBJECTIVES: ANCA-associated glomerulonephritis (ANCA-GN) is an immune-mediated kidney disease leading to acute or chronic renal failure. This study in...

Limitation of existing GFR estimating equations and application of artificial intelligence in improving GFR estimation and chronic kidney disease progression in people with diabetes.

The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2009 equation is the most commonly used equation for estimating glomerular filtration ...

Letter to the Editor: Evaluation of an artificial intelligence model based on multiparametric transrectal ultrasound for localising clinically significant prostate cancer by simulation of targeted biopsies.

Reply to the Letter to the Editor: Evaluation of an artificial intelligence model based on multiparametric transrectal ultrasound for localizing clinically significant prostate cancer by simulation of targeted biopsies.

Artificial intelligence-derived transition zone PSA density as a triage tool to reduce unnecessary prostate systematic biopsies in MRI-negative men.

OBJECTIVES: The study aimed to assess the predictive performance of transition zone PSA density (TZ-PSAD) compared to conventional PSA density (PSAD) ...

Causal modeling of chronic kidney disease in a participatory framework for informing the inclusion of social drivers in health algorithms.

OBJECTIVES: Incomplete or incorrect causal theories are a key source of bias in machine learning (ML) algorithms. Community-engaged methodologies prov...

Predicting renal-cell carcinoma recurrence after partial nephrectomy: a CT-radiomics approach.

BACKGROUND: About 30-40% of patients with renal-cell carcinoma experience recurrence within 5 years after partial nephrectomy despite current prognost...

RAMA: implementing Machine Learning to develop mortality risk prediction models for NICU patients with Acute Kidney Injury.

BACKGROUND: Acute Kidney Injury (AKI) is common in neonates admitted to the Neonatal Intensive Care Unit (NICU). Neonatal AKI is associated with multi...

Renal graft imaging: An update and overview.

Imaging of renal graft function and pathology, including delayed graft function (DGF), often requires a multimodal approach. The existing literature d...

Comparing Generative Artificial Intelligence vs Experts for Detection of Catheter-Associated Urinary Tract Infection.

A retrospective cohort study compared generative artificial intelligence (GenAI) versus infection control expert for catheter-associated urinary tract...

Updates on Kidney Transplantation From the World Transplant Congress 2025.

The World Transplant Congress 2025 showcased pivotal advances shaping the future of transplantation. Global efforts to expand access to transplantatio...

Deep Learning Identification of Clear Cell Renal Cell Carcinoma on MR Imaging.

OBJECTIVE: To investigate the performance of various convolutional neural networks (CNNs) in identifying clear renal cell carcinoma (ccRCC) on MRI and...

Identification of Key Physicochemical Characteristics Which Influence Epithelial-to-Mesenchymal Transition of Lung Cells after Exposure to Engineered and Natural Stone Dusts via a Hybrid Machine Learning Approach.

Exposure to respirable and inhalable dust from engineered stone is linked to lung diseases such as silicosis and COPD, yet the physicochemical propert...

Exploring the toxicological impact of N-nitrosodimethylamine (NDMA) exposure on bladder urothelial carcinoma (BLCA) through network toxicology, machine learning, and multi-dimensional bioinformatics analysis.

BACKGROUND: N-Nitrosodimethylamine (NDMA), classified as a Group 1 carcinogen by the International Agency for Research on Cancer (IARC), is ubiquitous...

Exfoliated kidney cells from urine for non-invasive kidney transplant monitoring: A potential opportunity?

Kidney transplantation is usually the optimal treatment option for patients living with kidney failure given its associations with improved survival, ...

Cardiovascular Risk Assessment Tools in Chronic Kidney Disease.

Cardiovascular (CV) risk calculators estimate the likelihood of CV events by integrating factors such as age, sex, blood pressure, lipids, smoking, an...