Urology

Automating prostate biopsy guidance: A robust CNN approach for non-rigid 3D/3D MR-TRUS image registration.

Fusing transrectal ultrasound (TRUS) and magnetic resonance (MR) images has significantly improved the accuracy of prostate cancer detection during targeted biopsies. However, automatic MR-TRUS registration remains challenging due to the large anatomical and appearance differences between the two imaging modalities. This study introduces a fully automatic, weakly supervised deep learning (DL) appr...

ReTri: Progressive domain bridging via representation disentanglement and triple-level consistency-driven feature alignment for unsupervised domain adaptive medical image segmentation.

Unsupervised domain adaptation (UDA) in medical image segmentation presents significant challenges due to substantial cross-domain disparities and the inherent absence of target domain annotations. In this study, to address these challenges, we propose an end-to-end progressive domain bridging framework based on representation disentanglement and triple-level consistency-driven feature alignment, ...

Machine learning-based multi-class classification of bladder pathologies using fused 3D CT radiomic and 3D auto-encoder deep features.

OBJECTIVE: To develop an automated analytical framework that integrates hybrid radiomics and deep learning features from non-contrast CT images for th...

Beyond the Cell Atlas: Functional Communities as the Essential Pathologic Units Driving Kidney Disease.

Kidney disease represents a growing global health crisis, demanding a deeper understanding of its underlying pathophysiology. Current mechanistic effo...

FGA Serves as a Potential Diagnostic Marker and Therapeutic Target for Elderly Acute Kidney Injury.

To identify potential biomarkers and explore the underlying mechanisms of elderly acute kidney injury (e-AKI), we performed integrative plasma proteom...

Challenges in improving the equation for estimating 24-h urinary sodium excretion from casual urine in hypertensive patients taking antihypertensive drugs: addressing overestimation, especially at low sodium excretion levels.

The estimation formula by Tanaka et al. for predicting the 24-h urinary sodium (Na) excretion (24Na) from a single causal urine sample is widely used....

Cross-omics interpretable neural network for discovery of molecular markers in prostate cancer.

Determining molecular markers that mediate clinically aggressive phenotypes in prostate cancer is a significant challenge. While traditional linear mo...

Authentic or Algorithm? Assessing the Use of Generative Artificial Intelligence in Urology Residency Personal Statements.

Patient Perceptions of Artificial Intelligence-Generated Kidney Transplant Information: Comparing ChatGPT With the National Kidney Foundation.

RATIONALE & OBJECTIVE: Generative artificial intelligence (AI) may help patients better understand the complexities of kidney transplantation. However...

Significance and Implications of Prostate Cancer: Critical Overview for Future Directions in Africa.

Prostate cancer places a heavy economic burden on health care in many countries globally. This is no exception in Africa. It is also described as one ...

Uncovering the potential of pathomics: prognostic prediction and mechanistic investigation of pancreatic cancer.

A machine learning-based pathomics model was investigated for its value and biological significance in predicting overall survival (OS) after surgery ...

Expansion of CKD diagnostics through biosensor technology: An early detection approach.

Chronic kidney disease (CKD) is a complicated global health disease that causes serious health issues like kidney failure and heart-related problems. ...

Effects of a transformer-based AI-based application to support incontinence-associated dermatitis and pressure injury assessment, nursing care and documentation: Controlled pilot intervention study.

BACKGROUND: Artificial intelligence (AI) is playing an increasingly important role in nursing care, including wound management. Differentiating pressu...

Machine learning model for predicting interfraction motion of the seminal vesicles in prostate cancer radiotherapy.

BACKGROUND AND PURPOSE: In external beam radiotherapy for prostate cancer, inclusion of the seminal vesicles (SV) in the clinical target volume (CTV) ...

Acute kidney injury: Detection, risk stratification, and predictive biomarkers.

BACKGROUND: Acute kidney injury (AKI) is a complex multifactorial syndrome characterized by a rapid decline in kidney function, frequently observed in...

Discovery of PPARγ Partial Agonists for Treatment of Type 2 Diabetes Based on an Integrated Virtual Screening Strategy that Combines Fragment Molecular Orbital Calculations, Machine Learning, Molecular Docking, Interaction Fingerprint Filtering, and Molecular Dynamics Simulations.

Peroxisome proliferator-activated receptor γ (PPARγ) is a key therapeutic target for type 2 diabetes and cardiovascular diseases due to its central ro...

Active surveillance as the treatment of choice for low-risk prostate cancer: Reliability of results obtained through clinical language processing systems and big data.

INTRODUCTION: Advances in natural language processing (NLP) technologies have gained prominence for extracting relevant clinical information. Savana i...

The role of focal therapy for localized prostate cancer: From diagnosis to ablation.

INTRODUCTION: Focal therapy (FT) has emerged as an intermediate therapeutic strategy between active surveillance (AS) and radical treatments for the m...

The role of artificial intelligence in hypertension management.

PURPOSE OF REVIEW: Hypertension remains a leading modifiable risk factor for cardiovascular and renal conditions and dementia. Given its rising global...

Corrigendum to "Geometric evaluation of a deep learning method for segmentation of urinary OARs on magnetic resonance imaging for prostate cancer radiotherapy". [Clin. Transl. Radiat. Oncol. 56 (2026) 101091].

[This corrects the article DOI: 10.1016/j.ctro.2025.101091.].