Urology

Cytokine-induced killer (CIK) Cells-associated transcriptome signature reveals the potential immunomodulatory role of TNFSF14 in clear cell renal cell carcinoma.

Among adoptive immune cell therapies, cytokine-induced killer cell (CIK) therapy has demonstrated clear therapeutic relevance in multiple cancers, particularly clear cell renal cell carcinoma (ccRCC). Despite being clinically successful, the molecular signatures associated with the immune-regulatory role of these CIK cells in cancers remain elusive. Considering this, we systematically identified C...

Interpretable machine learning models for bladder cancer overall survival prediction development and external validation via SEER database and Chinese cohort analysis.

OBJECTIVE: We developed interpretable machine learning(ML) models to predict overall survival in bladder cancer patients. This approach aims to improve the interpretability and transparency of our modeling results. METHODS: We collected clinical and pathological information on bladder cancer patients from the SEER database, allocating it to training and validation sets in a 7:3 ratio. At the same ...

Development of an integrated multidimensional nomogram for predicting stone-free status after retrograde intrarenal surgery: a machine learning-based approach.

BACKGROUND: This study aimed to develop and validate a novel preoperative nomogram to predict stone-free status (SFS) in patients undergoing retrograd...

Artificial Intelligence Remote Patient Monitoring for Predicting Overall Survival for Patients Undergoing Radical Cystectomy for Bladder Cancer: Exploratory Analysis of the Prospective Trial.

BACKGROUND: Previous studies have highlighted the benefits of using artificial intelligence-powered remote patient monitoring (AI RPM) in detecting he...

Postangiography Prediction of Renal Replacement Therapy in Acute Myocardial Infarction-Related Cardiogenic Shock: Least Absolute Shrinkage and Selection Operator Nomogram Development and Validation.

BACKGROUND: Acute kidney injury critically impacts outcomes in cardiogenic shock secondary to acute myocardial infarction (CS-AMI). Acute kidney injur...

Explainable AI in Cancer Imaging: Scoping Review of Methods, Modalities, and Clinical Integration.

BACKGROUND: Explainable artificial intelligence (xAI) is increasingly used in medical imaging to enhance transparency, clinical interpretability, and ...

RADIANT: A fully configurable radiotherapy dose prediction framework.

Treatment planning is a multi-disciplinary effort that requires medical decision-making, specialized training, and access to specialized software. Rec...

Attention-Based Point Cloud Completion for CT-Equivalent Kidney Volumetry from Tracked Freehand Ultrasound.

Kidney volume measurement is critical for managing polycystic kidney disease and monitoring transplants, but computed tomography involves radiation an...

Machine learning-based risk prediction model for postoperative acute kidney injury in surgical patients with chronic kidney disease (CKD): development, validation, and SHAP-based explainability.

This study aimed to develop machine learning models to predict postoperative acute kidney injury (AKI) in surgical patients with pre-existing chronic ...

Editorial Comment on "The Current Role of Artificial Intelligence in Urology Training: A Review of Available Platforms and Their Potential Applications".

PneumoMLPred: Innovating Pneumonia Management with Guideline Adherence Review and Explainable Machine Learning-based Mortality Prediction - A single-centre retrospective study.

INTRODUCTION: Community-acquired pneumonia (CAP) is one of the leading causes of death globally. Changing antibiotic resistance profiles, paucity of r...

Novel biomarkers driving treatment selection in metastatic castration-sensitive prostate cancer: fundamentals of personalized clinical decision making.

INTRODUCTION: Prostate cancer is well known to be androgen-dependent, with growth directly relying on the androgen receptor signaling pathway. In fact...

[Artificial intelligence in daily urological care: results of the AI barometer].

BACKGROUND: Urological care in Germany is undergoing transformation, while novel technologies with artificial intelligence (AI) have the potential to ...

Reply to the Letter to the Editor: Artificial intelligence for prostate MRI screening-methodological considerations regarding reference standards and reader design.

Letter to the Editor: Artificial intelligence for prostate MRI screening-methodological considerations regarding reference standards and reader design.

Urinary copper is linked to regional cortical volume reductions in adolescents with major depressive disorder.

Major depressive disorder (MDD) is highly prevalent among adolescents, but its neurobiological mechanisms remain unclear. Neuroimaging studies have sh...

Development and validation of artificial intelligence-based model for bladder cancer immunophenotyping using whole slide images.

The classification of immunophenotypes in muscle-invasive bladder cancer (MIBC) is critical for predicting immunotherapy response and clinical outcome...

Rapid slide-level assessment of glomerular yield using virtual staining of unstained renal biopsy sections.

BACKGROUND: Renal biopsy remains the gold standard for the diagnosis of kidney diseases, and specimen adequacy is essential for reliable histopatholog...

The evolving PI-RADS paradigm.

Prostate MRI is central to the diagnostic pathway for prostate cancer (PCa), reducing unnecessary biopsies, improving the detection of clinically sign...

What are the views of cancer care administrators and clinicians in England on the use of a machine learning clinical decision support system (ML-CDSS) to predict patients' risk of hepatic and renal deterioration during chemotherapy? A qualitative study.

OBJECTIVE: To explore administrators' and clinicians' views on the factors that influence their use and adoption of a machine learning clinical decisi...