Urology

Development and validation of a machine learning model for predicting distant metastasis in patients with renal cell carcinoma: a population-based study.

BACKGROUND: Distant metastasis is the leading cause of death in renal cell carcinoma (RCC), yet accurate prediction tools remain lacking. We aimed to develop and validate a machine learning model to predict synchronous distant metastasis-defined as metastasis present at the time of initial diagnosis-in RCC. METHODS: We identified 106,448 RCC patients from the SEER database (2010-2020), divided int...

Comorbidities for Predicting Progression Independent of Relapse Activity in Multiple Sclerosis Treated With B-Cell Depletion.

BACKGROUND: Progression independent of relapse activity (PIRA) has been shown to account for a majority of the disability accumulation in relapsing-remitting multiple sclerosis (RRMS) patients treated with disease-modifying therapies. While comorbidities are common in MS and linked to disability progression, their role in PIRA remains unclear. We investigated whether comorbidities at treatment ini...

Marker-less Body Surface Registration with 3D imaging for Percutaneous Intervention with Smartphone Augmented Reality in Phantoms and in vivo.

PURPOSE: To evaluate the accuracy of automatic surface tracking registration with a smartphone augmented reality (AR) guidance system for percutaneous...

Artificial intelligence in urology training Enhancing annotation, feedback, and evaluation in robotic, laparoscopic, and endoscopic surgery.

INTRODUCTION: The integration of artificial intelligence (AI) into surgical training is rapidly evolving, driven by advancements in machine learning. ...

Automated vs. manual segmentation for small renal mass imaging.

INTRODUCTION: Automated segmentation using artificial intelligence (AI) has the potential to rapidly perform three-dimensional (3D) segmentation of sm...

Radiomics-Based Machine Learning versus the MAP Score for Predicting Haematocrit Decline after Laparoscopic Partial Nephrectomy.

OBJECTIVE: To evaluate and compare the ability of the Mayo Adhesive Probability (MAP) score and radiomics-based machine learning approaches to predict...

Artificial intelligence-assisted urine cytology based on the Paris System for Reporting Urothelial Carcinoma.

BACKGROUND: Urine cytology is a noninvasive and valuable tool for detecting urothelial carcinoma but suffers from variable sensitivity and observer de...

Exploring the potential targets and mechanisms of artemisinin in the treatment of diabetic kidney disease using network pharmacology and molecular docking.

Diabetic kidney disease (DKD) is a secondary glomerular disease caused by diabetes, and its incidence is increasing annually. Artemisinin is an organi...

Environmental Levels of Sodium p-Perfluorous Nonenoxybenzene Sulfonate Induce Nephritis in Renal Proximal Tubular Epithelial Cells via Modulation of Estrogen Signaling Pathways.

Sodium p-perfluorous nonenoxybenzene sulfonate (OBS), widely used as an alternative to per- and polyfluoroalkyl substances, has been implicated in tox...

Submanifold sparse convolutional networks for automated 3D segmentation of kidneys and kidney tumours in computed tomography.

Accurate delineation of kidney tumours in Computed Tomography (CT) is essential for downstream quantitative analysis and precision oncology that could...

Artificial intelligence in cardio-kidney-metabolic care: Transforming integrated disease management through data-informed innovation.

Artificial intelligence (AI) is rapidly transforming the landscape of chronic medical conditions, such as cardio-kidney-metabolic (CKM) issues linked ...

A Cost-Efficient Multi-Angle Fusion Deep Learning for Ultrasound Localization Microscopy.

Ultrasound localization microscopy (ULM) enables super-resolution imaging of microvascular structures by localizing microbubbles from clutter-filtered...

Prostate Targeting: Compact Robot With Harmonic Stepper Motors for MRI-Guided Needle Therapy.

The superior image quality and excellent contrast offered by Magnetic Resonance Imaging (MRI) make it an ideal tool for guiding interventional procedu...

Predicting Positive Surgical Margins in Robot-Assisted Prostatectomy Using Machine Learning Models.

OBJECTIVE: To develop a machine learning (ML) model predicting positive surgical margins (PSM) after robot-assisted radical prostatectomy (RARP). METH...

Enhancing urothelial carcinoma diagnosis with artificial intelligence-integrated urine cytology: Biopsy-validated accuracy and efficiency gain.

BACKGROUND: Urine cytology is a noninvasive tool for detecting urothelial carcinoma, yet its performance depends heavily on expert cytologists and tim...

Kidney health without borders: a multilingual kidney education platform.

Artificial Intelligence-Based Objective Evaluation of Nerve-Sparing Status Combined With Preserved Urethral Length Predicts Urinary Continence Recovery After Robot-Assisted Radical Prostatectomy.

OBJECTIVES: To evaluate nerve-sparing status objectively using an artificial intelligence method applied to intraoperative images and to determine whe...

Combining bioinformatics and machine learning to analyze and validate sepsis-related cell senescence genes and potential drugs.

Sepsis is a life-threatening organ malfunction induced by the host's abnormal reaction to infection. Sepsis can induce cellular senescence, thereby ex...

Explainable artificial intelligence in prostate cancer treatment recommendation: A decision support system for oncological expert panels.

BACKGROUND: Therapeutic decisions in clinical oncology are commonly established through interdisciplinary consensus in multidisciplinary cancer confer...

Frequency-Specific Alterations of Spontaneous Brain Activity in Stroke Patients with Upper Limb Motor Dysfunction: A Multi-Metric rs-fMRI and Machine Learning Study.

BACKGROUND: Post-stroke upper limb motor dysfunction is associated with complex alterations in brain function, but the frequency-specific characterist...