Urology

Oxidative stress reprograms benign prostatic hyperplasia microenvironments: insights from integrative multi-omics and machine learning.

BACKGROUND: Oxidative stress (OS) is increasingly implicated in benign prostatic hyperplasia (BPH), yet the underlying cellular programs remain unclear. We integrated multi-omics and machine learning to identify OS-associated biomarkers and to characterize OS-linked stromal states, with targeted experimental validation. METHODS: Two bulk transcriptomic datasets (12 BPH, 16 controls) were integrate...

Leveraging untargeted metabolomics in combination with machine learning to uncover novel insights into bladder cancer.

Optimization Design and Bending Hysteresis Compensation of a Flexible Ureteroscopy Robot.

BACKGROUND: Ureteroscopic lithotripsy is a minimally invasive surgical procedure used to treat kidney stones. It faces challenges like a long learning...

Models Integrating Disease Heterogeneity and MPA Exposure Predict Systemic and Renal Efficacy of Mycophenolate in Pediatric Lupus Nephritis.

OBJECTIVES: This study aimed to develop and validate integrated prediction models for pediatric lupus nephritis (LN) treated with a mycophenolate mofe...

Artificial intelligence in nongynecologic cytology: A systematic review of current research and commercial tools.

BACKGROUND: Nongynecologic (non-GYN) cytology plays an important role in cellular and molecular cancer diagnosis, although its use is limited by varia...

Multicentre Evaluation of an AI-Assisted Urine Test for Clinically Significant Prostate Cancer in Men Undergoing Initial Biopsy.

The Extracellular Vesicles Gene-based Prostate Score (EGPS), powered by DeepSeek, is an artificial intelligence (AI) diagnostic tool that enhances the...

CT data harmonization via learned virtual monoenergetic imaging for cross-kV scan translation and radiomics reproducibility.

BACKGROUND: Radiomics extracts quantitative imaging features from computed tomography (CT) data for clinical decision-making. However, variations in a...

Pre-heart failure in early chronic kidney disease: clinical epidemiology and treatment.

Chronic kidney disease (CKD), defined per the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines by persistent (≥3 months) abnormalities of ...

Decoding chemical composition of urinary crystals from ultrasonic echo signals via deep learning.

Testosterone-Sparing Treatment Strategies for Biochemically Recurrent Prostate Cancer After Radical Prostatectomy.

PURPOSE OF REVIEW: Biochemical recurrence (BCR) after radical prostatectomy occurs in up to one-third of patients and increases the risk of metastasis...

AI-assessed sarcopenia as an independent predictor of neoadjuvant chemotherapy outcomes in muscle-invasive bladder cancer.

PURPOSE: Sarcopenia has already been widely investigated as a potential indicator of negative outcomes in oncology patients. Our aim was to evaluate t...

KidMesh: Computational Mesh Reconstruction for Pediatric Congenital Hydronephrosis Using Deep Neural Networks.

Pediatric congenital hydronephrosis (CH) is a common urinary tract disorder, primarily caused by obstruction at the renal pelvis-ureter junction. Magn...

Identification of a personalized eGFR threshold improves the prediction of kidney failure risk after transplantation.

BACKGROUND: Many factors cause kidney transplant graft failure. To identify at-risk patients and tailor treatment, failure risks must be accurately pr...

Predictive accuracy of a perioperative hemodynamic indices-based prediction model for moderate-to-severe acute kidney injury after orthotopic heart transplantation.

BACKGROUND: Acute kidney injury is a common complication after orthotopic heart transplantation. Previous models have failed to consider the impact of...

BD-KDD: A real-world clinical dataset for kidney disease diagnosis and healthy classification.

Kidney disease is a major global health concern that requires timely diagnosis and effective monitoring to prevent severe complications and improve pa...

Patient perspectives on the use of artificial intelligence to support treatment decision making in renal cancer: findings from the KATY project.

Accelerating organic luminescent material discovery: from quantum chemical calculations to machine learning.

Organic luminescent materials have attracted significant attention for their pivotal roles in optoelectronic devices, chemical sensing, and biomedical...

Concurrent AI-human interaction in prostate cancer MRI interpretation: More hype than help?

OBJECTIVE: We evaluated a commercial artificial intelligence (AI) system as a concurrent decision-support tool for clinically significant prostate can...

Development of Machine Learning Models for Predicting Prostate Cancer in Biopsy Candidates Using Prostate-Specific Antigen, Magnetic Resonance Imaging, and Hematologic Parameters.

INTRODUCTION: Prostate-specific antigen (PSA) alone is insufficient for the diagnosis of prostate cancer (PCa), particularly within the gray zone rang...

A Bilayer Feature Fusion Framework for Pan-Cancer Survival Prediction Based on Multihead Attention and Adaptive Differential Privacy: Model Development and Validation Study.

BACKGROUND: In the field of precision medicine, pan-cancer survival prediction is crucial for individualized oncology diagnosis and treatment. Althoug...