Urology

Advanced prediction of cardiovascular-kidney-metabolic syndrome using eight machine learning models and 24 composite indices.

AIM: This study aimed to construct and validate a machine learning classifier for cross-sectionally stratifying existing cardiovascular-kidney-metabolic (CKM) syndrome stages using routine composite inflammatory, metabolic and anthropometric indices, and to interpret core driving biomarkers via SHAP analysis. METHODS AND RESULTS: We analyzed data from 12,106 participants from the National Health a...

Artificial Intelligence Versus Conventional Methods for NCCN Risk Stratification in Localized Prostate Cancer (2020-2025): A Systematic Review.

BACKGROUND AND OBJECTIVE: Accurate risk stratification in localized prostate cancer is essential for guiding treatment decisions. Conventional National Comprehensive Cancer Network (NCCN) risk groups rely on prostate-specific antigen (PSA), Gleason grade group, and clinical stage, while artificial intelligence (AI) methods, including radiomics, digital pathology, and multimodal prediction models, ...

Diagnostic potential of B-cell translocation gene 2 in IgA nephropathy: Insights from molecular mechanisms.

IgA nephropathy (IgAN) is a prevalent glomerular disease characterized by IgA deposition, chronic inflammation, and fibrosis, leading to end-stage ren...

Evaluation of Generative Artificial Intelligence Models in Producing Anatomically Accurate Illustrations: A Comparative Study of Text-to-Image Generators.

Generative artificial intelligence (GAI) is increasingly being applied in biomedical sciences and medical education, including anatomy, where text-to-...

Comparison of large language models in the management of pediatric ureteropelvic junction obstruction: a comparative analysis of 125 clinical scenarios.

PURPOSE: To evaluate and compare the clinical accuracy, reliability, comprehensiveness and readability of three prominent Large Language Models (LLMs)...

Development and validation of a LightGBM based machine learning model for predicting postoperative erectile dysfunction after robot assisted radical prostatectomy: a multicenter cohort study.

Postoperative erectile dysfunction remains a highly debilitating complication following robot assisted radical prostatectomy for localized prostate ca...

Global research trends and hotspots in robotic-assisted prostate biopsy: a bibliometric analysis from 2008 to 2026.

Robotic-assisted prostate biopsy is now a key approach for early, accurate prostate cancer detection. The swift expansion and diversification of studi...

Multi-DECT image-based intra- and peritumoral interpretable radiomics and artificial intelligence models for preoperative prediction of pathological grading of non-muscle-invasive bladder cancer.

BACKGROUND: This study aimed to evaluate the predictive model based on multi-dual-energy computed tomography (DECT) imaging parameters and model integ...

Technical advancements in robot-assisted radical prostatectomy: systematic review and bibliometric analysis.

Robot-assisted radical prostatectomy has transformed the surgical management of localized prostate cancer, yet its research landscape remains incomple...

Artificial intelligence-based model for identifying anatomical and surgical structures in the videos of laparoscopic left hemicolectomy.

BACKGROUND: Precise surgical procedures are critical to improving the survival outcomes for colon cancer patients. Currently, there is no dedicated in...

Comment on "Comprehensive analysis of 55,213 stones: understanding common morphological associations advances endoscopic stone recognition and AI integration".

Exploratory clinical-CT machine learning characterization of CK7 expression in clear cell renal cell carcinoma.

BACKGROUND: Cytokeratin 7 (CK7) expression in clear cell renal cell carcinoma (ccRCC) may reflect tumor phenotype and biological heterogeneity, but it...

Association of Histological Features of Cortical and Medullary Peritubular Capillaries With Progressive CKD.

RATIONALE & OBJECTIVE: Peritubular capillary (PTC) rarefaction occurs in chronic kidney disease (CKD), but the independent association of PTC histolog...

Deciphering the phonon scattering mechanism and lattice thermal conductivity of La2Zr2O7 pyrochlores through point defect engineering: insights from molecular dynamics simulations with machine learning potentials.

The moment tensor potentials (MTPs) are trained, tested and validated for various single- and mixed-type point defects in La2Zr2O7 pyrochlores using t...

A serum-clinical composite model for prostate cancer diagnosis: multicenter validation and CRISPR/Cas13a-based detection.

BACKGROUND: Avoidable prostate biopsies remain a persistent weakness of prostate specific antigen (PSA)- and imaging-led prostate cancer (PCa) diagnos...

Mechanistic study on comorbidities of kidney stones and sepsis using transcriptome sequencing combined with single-cell spatial transcriptome sequencing.

Kidney stones and sepsis have a complex pathological association. Urinary obstruction and infection caused by kidney stones can easily induce sepsis, ...

Machine learning models of depressive symptoms in middle-aged and elderly patients with chronic kidney disease: A cross-sectional study based on CHARLS.

This study aimed to develop and compare the performance of machine learning models in identifying depressive symptom status among middle-aged and elde...

Evaluating the quality, understandability, actionability, and readability of ChatGPT-generated patient information on overactive bladder: A cross-sectional study.

This cross-sectional study aimed to evaluate the quality, understandability, actionability, and readability of patient-oriented information generated ...

Precision Medicine for Anticoagulation Strategies in the Cath Lab: Part 2.

PURPOSE OF REVIEW: Intraprocedural anticoagulation during percutaneous coronary intervention (PCI) remains particularly challenging in high-risk and u...

Interpretable machine-learning survival prediction of breast cancer prognosis from lifestyle factors: evidence from UK biobank.

BACKGROUND: Understanding how lifestyle habits influence breast cancer survival is crucial for improving long-term outcomes and guiding individualized...