Urology

Development and internal validation of a clinical prediction model for hemodialysis-related headache using LASSO and Boruta feature selection.

A common neurological symptom in dialysis patients is hemodialysis-related headache (HRH), which can result in premature hemodialysis termination and cause patients to decline hemodialysis. Predictors of headache have not been identified. One of our objectives is to create a nomogram that can accurately predict headaches in hemodialysis patients. Between 1 January 2023 and 31 October 2024, we retr...

Association of the CHG Index with the onset, progression, and prognosis of cardiovascular-kidney-metabolic syndrome: findings from two large prospective cohorts.

BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome represents a composite disease state driven by glucose and lipid metabolic dysregulation. The Cholesterol, High-density lipoprotein, and Glucose (CHG) index reflects the composite burden of these metabolic factors. However, its impact on the onset, stage-wise progression, and prognosis of CKM syndrome remains unclear. METHODS: This study u...

[18F] PSMA-3Q PET/CT radiomics at 45% SUVmax threshold: predicting post-surgical ISUP grade ≥ 4 and extraprostatic extension for noninvasive stratification in prostate cancer management.

OBJECTIVE: To systematically evaluate radiomic features extracted from [18F] PSMA-3Q PET/CT using 40%, 45%, and 50% SUVmax thresholds for their abilit...

Clinical investigation of a digital biomarker for joint swelling in inflammatory arthritis based on automated quantification of dorsal finger fold patterns.

This study aimed to clinically evaluate a digital biomarker, the Finger Fold Index (FFI), derived from the ratio of joint diameter to finger fold surf...

Predicting and explaining poor prognosis in diabetic kidney disease using SHAP-based interpretable machine learning.

Prognostic assessment of diabetic kidney disease (DKD) is essential for personalized management. This study developed eight machine learning models us...

Multimodal Artificial Intelligence Prediction of Abiraterone Efficacy in Two STAMPEDE Phase 3 Trials of Non-Metastatic Very High-Risk Prostate Cancer.

BACKGROUND: Long-term androgen deprivation therapy (LT-ADT) with radiotherapy is standard-of-care for high-risk localized prostate cancer, with abirat...

Predictive modeling of urinary 8-hydroxy-2´-deoxyguanosine (8-OHdG) in metal workers: A comparative study of machine learning algorithms in toxicology.

Urinary 8-hydroxy-2´-deoxyguanosine (8-OHdG), a biomarker for oxidative DNA damage, is commonly used to assess the repair of reactive oxygen species (...

AI Chatbot Answers for Drug Dosing Adjustments According to Renal Function in Geriatric Patients Using the New Scoring System (AI Quality Output Score): Cross-Sectional Study.

BACKGROUND: Preventable adverse drug reactions in geriatric patients are caused by overdosing, especially in cases of impaired renal function. Artific...

Predicting End-Stage Renal Disease and Mortality in Chronic Kidney Disease Using Machine Learning: Retrospective Cohort Study.

BACKGROUND: Chronic kidney disease (CKD) is a global health burden characterized by heterogeneous progression trajectories. Without timely and appropr...

Artificial intelligence in prostate cancer imaging: A mini-review of current applications and future directions.

This mini-review synthesizes evidence from recent studies to provide an updated perspective on current applications, methodological challenges, and fu...

Targeting the intrinsically disordered AR-NTD through a machine learning-based enhanced sampling workflow.

Targeting the intrinsically disordered N-terminal domain of the androgen receptor (AR-NTD) represents a promising strategy to overcome resistance in p...

Deep learning based on multiparametric MRI for differentiating benign from malignant PI-RADS 3 prostate lesions: a dual-center study.

To address the diagnostic challenge of indeterminate PI-RADS 3 prostate lesions, we developed a non-invasive deep learning radiomics model using multi...

Deep learning models built from PSMA PET of the primary tumor can predict synchronous and metachronous prostate cancer metastases.

OBJECTIVE: The objective was to develop prognostic models that included convolutional neural networks (CNN) derived from 18F-DCFPyL (PSMA) PET imaging...

A decision-oriented framework for genomic testing across the prostate cancer continuum.

Genomic testing is now embedded in contemporary prostate cancer care, yet the clinical meaning of different genomic platforms varies substantially by ...

Computational exploration of quercetin derivatives from Azadirachta indica leaf as threonine tyrosine kinase inhibitors for potential lung and pancreatic cancer treatment.

Lung and pancreatic adenocarcinomas account for substantial cancer-related mortality worldwide, with current therapeutic efficacy severely limited by ...

Response to Comment on "Machine learning model for predicting interfraction motion of the seminal vesicles in prostate cancer radiotherapy".

Correction to "A deep-learning model using automatedperformance metrics and clinical features topredict urinary continence recovery afterrobot-assisted radical prostatectomy".

Navigating PI-RADS v2.1 in clinical practice: pitfalls, variability, and the supportive role of AI.

Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 has substantially advanced the standardization of prostate MRI acquisition, interpret...

Deep learning for clinically significant prostate cancer detection on MRI: a systematic review, HSROC meta-analysis, and direct comparison with PI-RADS-based interpretation.

OBJECTIVES: To estimate patient-level diagnostic accuracy of deep learning (DL) for MRI-based detection of clinically significant prostate cancer (csP...

Longitudinal serum uric acid transition patterns and their clinical, genetic, and dietary determinants: prospective prediction of incident hyperuricemia and gout in a Korean population-based cohort.

BACKGROUND: Longitudinal serum uric acid (SUA) transition patterns and their clinical, genetic, and dietary determinants remain poorly characterized. ...