Urology

Prediction of Benign and Malignant Small Renal Masses Using CT-Derived Extracellular Volume Fraction: An Interpretable Machine Learning Model.

RATIONALE AND OBJECTIVES: We developed a machine learning model comprising morphological characteris...

Diagnostic accuracy of machine learning approaches to identify psoriatic arthritis: a meta-analysis.

While machine learning (ML) approaches are commonly utilized in medical diagnostics, the accuracy of...

The urinary microbiome distinguishes symptomatic urinary tract infection from asymptomatic older adult patients presenting to the Emergency department.

Older adults suffer from a high rate of asymptomatic bacteriuria (ASB), in which urinalysis may appe...

Integrative analysis identifies FBXO5 as a critical mediator of CRPC progression and bone metastatic potential.

INTRODUCTION: Castration-resistant prostate cancer (CRPC) poses a major clinical challenge due to it...

Urinary Complement proteome strongly linked to diabetic kidney disease progression.

Diabetic kidney disease (DKD) progression is not well understood. Using high-throughput proteomics, ...

An evaluation of rectum contours generated by artificial intelligence automatic contouring software using geometry, dosimetry and predicted toxicity.

Objective This study assesses rectum contours generated using a commercial deep learning auto-co...

Quantum Federated Learning in Healthcare: The Shift from Development to Deployment and from Models to Data.

Healthcare organizations have a high volume of sensitive data and traditional technologies have limi...

Machine-Learning-Assisted Density Functional Theory Calculations: A New Approach to Screening Thermal Runaway Gas Sensors for Lithium-Ion Batteries.

Lithium-ion batteries face safety risks, such as spontaneous combustion and explosion, during long-t...

Artificial Intelligence-Assisted MRI Interpretation in Prostate Cancer: Supporting Confidence and Reducing Variability.

Incorporation of Metabolic Dysfunction-Associated Steatotic Liver Disease in the Health Stage of Cardiovascular-Kidney-Metabolic Syndrome Improves Predictive Ability for Coronary Artery Disease in a Japanese General Population.

BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome is a recently proposed condition encompas...

Considerations for Videourodynamics and How it Impacts Practice.

AIMS: Provide urologists with a comprehensive understanding to guide the optimal and evidence-based ...

Development and evaluation of deep neural networks for the classification of subtypes of renal cell carcinoma from kidney histopathology images.

Kidney cancer is a leading cause of cancer-related mortality, with renal cell carcinoma (RCC) being ...

Challenges and Opportunities in Psoriatic Disease: An Integrated View of the Future.

Psoriatic disease (PsD), which includes cutaneous psoriasis (PsO) and psoriatic arthritis (PsA), aff...

Improving Phase Stability of α-CsPbI through Combined Strain-Doping Engineering: Insights from First-Principles Calculations and Machine Learning.

The all-inorganic perovskite of cubic CsPbI (α-CsPbI) exhibited high thermal stability, owing to the...

Machine Learning-Enhanced Calculation of Quantum-Classical Binding Free Energies.

Binding free energies are key elements in understanding and predicting the strength of protein-drug ...

Practical Machine Learning Strategies 4: Using Neural Networks to Replicate Proton and C NMR Chemical Shifts Obtained from ωB97X-D/6-31G* Density Functional Calculations.

Described are neural networks that accurately reproduce proton and C chemical shifts obtained from ω...

AI-driven framework for automated detection of kidney stones in CT images: integration of deep learning architectures and transformers.

. Kidney stones, a prevalent urological condition, associated with acute pain requires prompt and pr...

Natural language processing for kidney ultrasound analysis: correlating imaging reports with chronic kidney disease diagnosis.

INTRODUCTION: Natural language processing (NLP) has been used to analyze unstructured imaging report...

The state of the art in artificial intelligence and digital pathology in prostate cancer.

Prostate cancer is among the most common cancers worldwide, with ~1.5 million new diagnoses globally...

Diagnostic systematic review and meta-analysis of machine learning in predicting biochemical recurrence of prostate cancer.

Prostate cancer (PCa) is the most prevalent malignant tumor in males, and many patients remain at ri...

Unsupervised machine learning approach to interpret complex lower urinary tract symptoms and their impact on quality of life in adult women.

PURPOSE: To identify clinically meaningful clusters of lower urinary tract symptoms (LUTS) in adult ...