Urology

Intratumoral and Peritumoral Fat CT‑Based Radiomics for Predicting Recurrence Risk in Non-Muscle-Invasive Bladder Cancer: A Two-Center Study.

BACKGROUND: Non-muscle-invasive bladder cancer (NMIBC) has a high risk of recurrence, and multiple surgeries increase the disease burden on patients. Using computed tomography (CT)-based machine learning, this study established a pre-treatment recurrence prediction model incorporating tumor and peritumoral fat characteristics. This approach may guide early clinical interventions. METHODS: In this ...

Loss of biomechanical features reveals smooth muscle disruption and disease progression in prostate cancer.

BACKGROUND: Biomechanical features show notable heterogeneity in tumor risk stratification, yet their role in prostate cancer (PCa) progression remains unclear. This study aimed to elucidate the role and underlying mechanism of biomechanical features in PCa progression. METHODS: We integrated transcriptomic data from 1693 PCa patients across ten public cohorts and single-cell RNA sequencing (scRNA...

Head-to-head comparison of the ability of the cardiometabolic index and triglyceride-glucose index to predict 3-year major adverse cardiovascular events in patients with atrial fibrillation: insights from a community cohort.

BACKGROUND: Atrial fibrillation (AF) represents the most common sustained cardiac arrhythmia and confers an elevated risk of major adverse cardiovascu...

Artificial intelligence (AI)-based multi-organ contour quality assurance with uncertainty estimation for online adaptive radiotherapy (oART).

Accurate delineation of treatment targets and organs at risk (OARs) is essential to the success of radiotherapy (RT). Although artificial intelligence...

Early management of acute heart failure.

PURPOSE OF REVIEW: Acute heart failure (AHF) is a frequent, high-risk emergency department presentation in which early diagnostic and therapeutic deci...

Machine Learning Prediction of Chronic Kidney Disease in Elderly MetS Patients Using NHANES 2011-2020 Data.

BACKGROUND: Chronic kidney disease (CKD) is getting more common in elderly people with metabolic syndrome, but early detection and risk prediction are...

Systemic Microvasculature Frailty: Brain frailty score predicts contrast-associated acute kidney injury after thrombectomy for stroke.

BACKGROUND: Contrast-associated acute kidney injury (CA-AKI) is a frequent complication after mechanical thrombectomy (MT). Cerebral small vessel dise...

Interpretable machine learning using CT radiomics predicts pathological upgrading after secondary resection in non-muscle-invasive bladder cancer.

BACKGROUND AND PURPOSE: Repeat transurethral resection (ReTUR) is essential for reducing residual and recurrent non-muscle-invasive bladder cancer (NM...

A chronic kidney disease prediction system based on Internet of Things using walrus optimized deep learning technique.

The Internet of Things (IoT) and cloud computing (CC) concepts are commonly incorporated in healthcare applications. In the healthcare industry, a hug...

Preoperative CT imaging and machine learning models for predicting ureteral access sheath placement success in non-stented patients with ureteral calculi: a retrospective cohort study.

OBJECTIVE: This study aims to both develop and evaluate a predictive model for ureteral access sheath(UAS)placement success using preoperative CT-base...

Development and Validation of a Urinary Exosomal miRNA Diagnostic Panel for Early Detection of Esophageal Cancer.

Esophageal squamous cell carcinoma (ESCC) remains a leading cause of cancer-related mortality, with early detection being challenging. Although endosc...

Morphometric analysis and its application in lupus nephritis: a systematic review.

Lupus nephritis (LN) is a severe manifestation of systemic lupus erythematosus (SLE), characterized by marked histological heterogeneity and high inte...

UroFusion-X: a unified multimodal deep learning framework for robust diagnosis, subtyping, and prognosis of urological cancers.

Multimodal clinical data, including imaging, pathology, omics, and laboratory tests, are often fragmented in routine practice, leading to inconsistent...

Estimation of IPSS and OABSS scores using ChatGPT-4o: a comparative validation study in Korea.

PURPOSE: To evaluate the performance of ChatGPT-4o in estimating International Prostate Symptom Score (IPSS) and Overactive Bladder Symptom Score (OAB...

MRI-based patient selection for active surveillance in prostate cancer using U-Found: a generalized deep learning model.

Deformable Point Cloud Registration-Based Bidirectional Local Distance (DPCR-BLD): A Methodology for Systematic Evaluation and Visualization of Local Disagreements in Clinical Autocontouring.

PURPOSE: Variability in autosegmentation can arise from the training data, leading to disagreements with clinical practice. The anisotropic and locali...

ASO Author Reflections: Multimodal Deep Learning Redefining Precision Prognosis in Prostate Cancer.

Gene Modification: Exploring the potential in treating kidney diseases.

Chronic kidney disease (CKD) is a leading cause of death worldwide. Currently available drugs slow but do not cure or prevent progression to end-stage...

Using Latent Dirichlet Allocation Topic Modeling to Uncover Latent Research Topics and Trends in Renal Cell Carcinoma: Bibliometric Review.

BACKGROUND: Renal cell carcinoma (RCC) is a common, often lethal kidney cancer that originates in the renal cortex. Its incidence is rising, and major...

Institution-specific pre-treatment quality assurance control and specification limits: a tool to implement a new formalism and criteria optimization using statistical process control and heuristic methods.

OBJECTIVE: Establishing control and specification limits for Volumetric Modulated Arc Therapy (VMAT) pre-treatment quality assurance (PTQA) is essenti...