Urology

A fatty acid metabolism-based deep learning model predicts biochemical recurrence and identifies NUDT19 as a candidate metabolic factor in prostate cancer.

PURPOSE: To develop a fatty acid metabolism-based deep learning model for predicting biochemical recurrence (BCR) in prostate cancer (PCa) and to identify recurrence-associated metabolic regulators. METHODS: Transcriptomic data from TCGA and GEO GSE70769 were integrated to identify fatty acid metabolism-related genes and construct a deep learning model for BCR prediction. Tumor-infiltrating lympho...

Impact on Cost and Expert Time of Data-Efficient Deep Learning for Medical Image Segmentation.

Purpose To develop and systematically evaluate an iterative training approach, termed the expert-guided annotation loop, for efficient reference standard medical image segmentation, including assessment of two sample-selection strategies and real-world clinical implementation. Materials and Methods This retrospective study included ten datasets comprising 1948 CT or MRI examinations from autosomal...

[Beyond the bladder-a specialty rediscovering itself: Outpatient. Networked. Digital].

BACKGROUND: Urology is undergoing a fundamental transformation characterized by increasing outpatient care, digitalization, and cross-sectoral network...

[Between catheters and artificial intelligence: High-tech urology-where manual skills meet digital expertise].

Artificial intelligence (AI) in urology has evolved from an experimental technology to a relevant component of clinical processes. While early applica...

Elucidating the therapeutic targets and multi-target mechanisms of salvianolic acid A for diabetic nephropathy.

Diabetic nephropathy (DN) is a leading cause of chronic kidney disease. Salvianolic acid A (SAA) has shown promising therapeutic potential against DN,...

Frailty index and type 2 diabetes with renal complications: insights from Mendelian randomization and retrospective observational study.

OBJECTIVES: To investigate the relationship between frailty and diabetic kidney disease (DKD)-related renal complications using Mendelian randomizatio...

Validation of online clearance monitoring and machine learning-based prediction of dialysis adequacy in Vietnamese hemodialysis patients: a cross-sectional study.

BACKGROUND: Online clearance monitoring (OCM) offers non-invasive real-time dialysis adequacy assessment, but validation data from Southeast Asian pop...

Multi-omics integration and clinical validation identify CKAP2 as a diagnostic biomarker for bladder cancer.

BACKGROUND: Bladder cancer (BC) remains a prevalent malignancy with a high recurrence rate; however, the lack of specific biomarkers hinders early det...

Development of an Interpretable Machine Learning Model for Predicting Clavien-Dindo Grade ≥2 Complications after Unilateral Minimally Invasive Pyeloplasty in UPJO: A Retrospective Cohort Study.

BACKGROUND: Minimally invasive pyeloplasty (MIP), encompassing both conventional laparoscopy and robot-assisted approaches, has become the primary tre...

Predicting Renal Tumor Pathology from Intraoperative Gross Appearance: An AI-Based Pilot Study.

OBJECTIVE: To evaluate the feasibility of using convolutional neural networks (CNNs) and vision transformers (ViTs) to predict renal tumor pathology i...

Deep learning for intraoperative recognition of critical structures in total hysterectomy.

BACKGROUND: This study aimed to develop and evaluate a deep learning-based surgical navigation system capable of recognizing the ureter, uterine arter...

PCT-Anchored Machine Learning for Pre-Culture Identification of Gram-Negative Sepsis in Children: A Four-Site Study.

OBJECTIVE: Procalcitonin (PCT) has moderate accuracy for bacteremia detection but is infrequently used in pediatric emergency departments, partly due ...

Emerging robotic platforms in urologic surgery: a bibliometric and visualization analysis of global trends and research hotspots.

Robot-assisted surgery has become an important component of modern urologic practice, and the emergence of alternative robotic platforms has accelerat...

Non-linear impact mechanisms of multi-modal urban traffic on air quality: An interpretable machine learning study for sustainable policy making.

Urban air pollution, specifically Nitrogen Dioxide (NO2), presents a multifaceted challenge that is intricately coupled with the stochastic, multi-mod...

From black box to glass box: explainable artificial intelligence for acute kidney injury prediction-a scoping review and the GLASS-AKI translational framework proposal.

BACKGROUND: Artificial intelligence models for acute kidney injury (AKI) prediction achieve strong discriminative accuracy, yet clinical adoption rema...

Automating standardization of prostate cancer biopsy and histopathology reports with privacy-preserving local large language models.

PURPOSE: Large-scale biomedical analysis in prostate cancer requires structured, tabular datasets, yet most clinical documentation remains in free-tex...

Interpretable machine learning model for predicting kidney failure among CAKUT children in multicenter large-scale study.

Congenital anomalies of the kidney and urinary tract (CAKUT) are the leading cause of pediatric kidney failure, but predicting individual progression ...

Evaluation of ChatGPT-4o's and DeepSeek R1's responses to urological problems: a comparative study.

BACKGROUND: Urology presents unique challenges for AI systems, requiring both extensive medical knowledge and advanced reasoning. While large language...

Global research trends and thematic evolution in fluorescence-guided robot-assisted urologic surgery: a bibliometric and visualized study.

Fluorescence-guided imaging has increasingly been integrated into robot-assisted urologic surgery to improve intraoperative visualization of vascular ...

Association between visceral adiposity index and delayed union/nonunion after tibial or femoral shaft fractures: a single-center retrospective cohort study.

BACKGROUND: Delayed union and nonunion remain clinically important complications after tibial and femoral shaft fractures. Although traditional risk f...