Urology

Association of cardiovascular-kidney-metabolic syndrome stages with MASLD prevalence and liver fibrosis severity: evidence from traditional and machine learning approaches.

INTRODUCTION: Cardiovascular-Kidney-Metabolic (CKM) syndrome reflects the convergence of cardiovascular, renal, and metabolic disorders. Metabolic dysfunction-associated steatotic liver disease (MASLD), as the hepatic phenotype of metabolic impairment, provides a critical link within this continuum. However, the association between CKM syndrome staging, MASLD prevalence, and liver fibrosis severit...

Practical integration of machine learning into ab initio calculations and workflows: Accelerating the SCF cycle via density matrix predictions.

Data-driven approaches offer great potential for accelerating ab initio electronic structure calculations of molecules and materials, but their transferability is often limited due to the vast amount of data needed for training, including the need to fine-tune universal models for each specific system to be studied. Here, we demonstrate how contributions from system-specific electronic structure m...

Construction of a deep learning-based predictive model for delayed graft function in kidney transplantation.

BACKGROUND: Delayed graft function (DGF) is a major complication of kidney transplantation that adversely affects long-term graft survival. This study...

Development of a Predictive Calculator for the Need for Abdominoperineal Resection after Chemoradiation Therapy in Anal Squamous Cell Carcinoma.

BACKGROUND: Chemoradiation therapy (CRT) is standard treatment for anal squamous cell carcinoma (ASCC). Abdominoperineal resection (APR) is usually re...

Long-Term Follow-Up in Liver Transplantation and Combined Cardiac Surgery: Validation and Refinement of the LT+CS Risk Score Using Advanced Machine Learning.

BACKGROUND: Combined liver transplantation (LT) and cardiac surgery (LT+CS) is a therapeutic option for patients with end-stage liver disease (ESLD) a...

Detection of prostate cancer in 3D pathology datasets via generative immunolabeling.

Recent advancements in nondestructive 3D pathology offer a complement to standard histology by enabling comprehensive volumetric analyses of intact cl...

Feasibility of Integrating Urinary Proteomics and Machine Learning for Diagnosing Diabetic Nephropathy.

Diabetic nephropathy (DN) represents the predominant microvascular complication associated with diabetes mellitus; however, existing diagnostic techni...

Artificial intelligence-assisted reading of non-contrast prostate MRI: application and concordance with expert interpretation in a screening population within the PROSA trial.

OBJECTIVES: Non-contrast MRI (bi-parametric MRI-bpMRI) has been investigated as a potential tool to be integrated in clinically significant prostate c...

Patients Are Generally Supportive of Artificial Intelligence in Breast Imaging: A Multisite Survey of Breast Imaging Patients.

OBJECTIVE: To understand the perspective of patients undergoing breast imaging on the use of artificial intelligence (AI) in breast cancer screening. ...

Early Risk Factor Prediction in Chronic Kidney Disease Diagnosis Using Feature Selection and Machine Learning Algorithms.

Chronic kidney disease, CKD in short, is a kind of long-term kidney illness in which rapid deterioration of kidney function is observed over a period ...

Predicting vesicoureteral reflux outcomes using artificial intelligence: A critical appraisal using APPRAISE-AI.

Vesicoureteral reflux (VUR) is a common congenital urinary tract anomaly in children, associated with recurrent urinary tract infections (UTIs) and lo...

Renal Clinical Study Participants Support Data Sharing and Use of Artificial Intelligence.

INTRODUCTION: Kidney diseases are a global health concern. Sharing data from renal clinical studies and the use of artificial intelligence (AI) can ad...

A deep learning and morphometric hybrid model for automated quantification of kidney interstitial fibrosis in trichrome-stained whole-slide image.

BACKGROUND: Interstitial fibrosis (IF) is the strongest predictor of chronic kidney disease progression. Visual estimation of IF from trichrome (TRI)-...

Research on the Application Value of Blood Plasma Autofluorescence Spectroscopy Model Constructed by Machine Learning Algorithms in Identifying the Types of Post-operative Kidney Transplantation Injury.

BACKGROUND: This study aimed to assess the value of blood plasma autofluorescence spectroscopy in classifying renal injury after renal transplantation...

Predicting Persistent Renal Failure Necessitating Dialysis in Patients Undergoing Elective, Open Thoracoabdominal Aortic Aneurysm Repair.

BACKGROUND: Acute renal failure remains a significant complication after open thoracoabdominal aortic aneurysm (TAAA) repair and is associated with hi...

The application of Machine learning in predicting the outcomes of minimally invasive treatments for uterine Fibroids: A systematic review and meta-analysis.

RATIONALE AND OBJECTIVES: Uterine fibroids (UFs) are common benign tumors that impact women's health, particularly through symptoms such as abnormal b...

[The Digital Lab: Practical digital workflow and integration of AI for routine in pathology, through the example of prostate cancer].

Digital pathology is a major technological revolution for pathology. It modernizes routine practices and paves the way for the integration of artifici...

Reinforcement learning-guided segment anything model for MRI prostate and dominant intraprostatic lesions auto-segmentation.

Objective. Accurate segmentation of the prostate and dominant intraprostatic lesions (DILs) on magnetic resonance imaging (MRI) is important for prost...

Automatic classification of kidney stone components based on smartphone microscopy and the GoogLeNet model.

BACKGROUND: To develop an automated classification system for urinary stone composition by integrating smartphone-based microscopic imaging (TIPSCOPE)...

Machine Learning Tools for Predicting Pediatric Urinary Tract Infections Caused by ESBL-producing Bacteria.

BACKGROUND: The prevalence of pediatric urinary tract infections (UTIs) caused by extended-spectrum β-lactamases (ESBL)-producing bacteria is increasi...