Urology

Characterizing the MSMP-CCR2 Interaction through Molecular Dynamics Simulations and Machine Learning Approaches.

The MSMP (MicroSeminoProtein, Prostate-associated) protein is overexpressed in several cancers, including prostate, ovarian, and breast cancers. Its overexpression is particularly prevalent in tumors resistant to hormonal therapy, as well as to antiangiogenic treatments (e.g., anti-VEGF therapies). In hypoxic tumor microenvironments, characteristic of solid tumors, MSMP expression increases and fa...

Development of a LASSO-based machine learning model for relapse prediction in lupus nephritis.

OBJECTIVE: To identify the predictors of renal relapse in patients with lupus nephritis (LN) and develop a predictive model. METHODS: The patients with LN who received renal biopsies from 2005 to 2024 in Xijing Hospital were enrolled. This study was designed as a cohort study. Clinical and serological characteristics at the time of renal biopsy, nephritis histology, the duration to remission and t...

Metabolic determinants of cancer immunotherapy outcomes identified by plasma profiling.

Immune-checkpoint inhibitors benefit a subset of patients with advanced cancer, and the metabolic determinants of response remain unclear. Here, using...

Feasibility of deep learning-accelerated ultrafast T1-weighted VIBE Dixon imaging of the pelvis for screening of metastases in prostate MRI.

OBJECTIVE: This study aims to assess the image quality and perceived diagnostic confidence of research deep learning (DL)-accelerated T1-weighted "vol...

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 iden...

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 stand...

[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...