Nephrology

Artificial intelligence versus classical scoring systems: a comparative analysis of stone-free prediction after percutaneous nephrolithotomy.

This study aimed to compare the predictive performance of traditional stone scoring systems with a l...

Microvascular inflammation in the kidney transplant, beyond acute antibody-mediated rejection.

PURPOSE OF REVIEW: Microvascular inflammation (MVI) is a central feature of allograft rejection, tra...

Frailty trajectories and risk of incident advanced CKM syndrome: A national cohort analysis.

BACKGROUND: The interplay between frailty dynamics and the newly defined Cardiovascular-Kidney-Metab...

Ultrasound-Based Kidney Stone Classification Using Kronecker Self-Organizing Map Forward Harmonic Network.

Kidney stone disease is a prevalent urological disorder that can result in severe pain, obstruction,...

Network toxicology and experimental validation reveal TDCPP as an emerging environmental risk factor for chronic kidney disease.

BACKGROUND: Tris(1,3-dichloro-2-propyl) phosphate (TDCPP) is a widely used organophosphorus flame re...

Unraveling heterogeneity in LUAD via multi-omics integration: molecular classification and therapeutic implications.

Lung adenocarcinoma (LUAD) displays significant morphological and molecular heterogeneity both withi...

Forecasting Waitlist Trajectories for Patients With Metabolic Dysfunction-Associated Steatohepatitis Cirrhosis: A Neural Network Competing Risk Analysis.

BACKGROUND: Metabolic dysfunction-associated steatohepatitis (MASH) cirrhosis is a leading indicatio...

Improving Robustness and Training Efficiency of Machine-Learned Potentials by Incorporating Short-Range Empirical Potentials.

Machine learning force fields (MLFFs) are powerful tools for materials modeling, but their performan...

Radiomics-based gradient boosting model on contrast-enhanced MRI for non-invasive prediction of epidermal growth factor receptor expression and therapeutic response to EGFR-targeted antibody-drug conjugates in high-grade glioma organoid models.

BACKGROUND: Epidermal growth factor (EGF) and its receptor EGF(EGFR) play crucial roles in glioblast...

Optimizing Early Detection of Diabetic Kidney Disease through Synergistic Biomarkers and Serum Metabolites in Human.

BACKGROUND: Diabetic kidney disease (DKD) progresses to end-stage renal disease more rapidly than ch...

Digital hypertension in 2024-2025: emerging evidence and future directions.

Recent advances in digital technology are remarkable, and they are driving profound transformations ...

Glomeruli detection and classification in histopathological images using deep learning semantic segmentation.

Advanced immunotherapy across diseases and the role of artificial intelligence: A review.

Immunotherapy, a therapeutic strategy aimed at modulating the host immune system, has undergone rapi...

Metabolic Syndrome and a Broken Heart: Trust Your Gut or Risk Your Heart.

Gut dysbiosis is increasingly recognized as a contributor to heart failure; however, its specific ro...

Development of a machine learning-based model for prediction of diabetes risk in patients with metabolic dysfunction-associated steatotic liver disease (MASLD).

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading chronic li...

A comprehensive multi-task deep learning model for kidney cancer: histological subtyping, clinical staging, and anatomical complexity grading.

OBJECTIVES: To develop and validate a multi-task deep learning (MTDL) model using multiphase contras...

Predicting and interpreting protein and phosphoprotein abundance from pan-cancer and single-cell transcriptomes.

Proteins that impact phenotype and disease are often approximated by RNA expression, which poorly in...

Effect of frailty status and histopathological features on upstaging of non-muscle-invasive bladder cancer: a critical analysis based on machine learning.

AIM: This study aimed to develop a machine learning (ML)-assisted model to predict the risk of upsta...

Machine learning-based prediction of three-year mortality in elderly inpatients with coronary artery disease combined with heart failure.

OBJECTIVE: Accurate prediction of survival outcome is essential for early intervention and treatment...

Beyond the Chill: Emerging Electrolytes, Cathodes, and Air Electrodes for Cryogenic Aqueous Zn Batteries.

The burgeoning demand for energy storage in extreme cold environments has accelerated global researc...

Designing with Li2S in Lithium-Sulfur Batteries: From Fundamental Chemistry to Practical Architectures.

Lithium-sulfur (Li-S) batteries deliver gravimetric energy densities considerably higher than those ...