Nephrology

An Integrated Clinical-Histopathologic Prediction Model for Cardiac Allograft Rejection: Translating Machine Learning into Clinical Risk Frameworks.

BACKGROUND: Cardiac allograft rejection (CAR) remains the leading cause of early graft failure after...

Personalized assessment of hyperuricemia probability in metabolic dysfunction-associated steatotic liver disease: construction and multicenter validation of a clinical nomogram.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease is increasingly recognized as a...

Classifying Kidney Tumor via Adaptive SE-ResNeXt With Mutli-Novel Loss Function and Renal Mass Segmentation Using Pyramidal Attention-Based R2Unet++ Model.

Kidney tumors are one of the prevalent types of tumor globally and it has become a significant healt...

SORBS2: A Molecular Nexus in Multisystem Diseases Through Scaffold-Mediated Regulation.

Sorbin and SH3 Domain Containing 2 (SORBS2), a multifunctional scaffold protein harbouring Sorbin ho...

Cross-attention multimodal fusion for EGFR mutation prediction: A predictive model using CT and whole-slide images.

BACKGROUND: The prediction of Epidermal Growth Factor Receptor (EGFR) mutation status in advanced lu...

Combined Effects of Long-Term Sulfur Dioxide Exposure and Environmental Heat Stress on the Risk of Kidney Stone Disease.

OBJECTIVES: Kidney stone disease is influenced by environmental, metabolic, and climatic factors. Al...

Multi-Omics and Machine Learning-Uncovered FLT1-Mediated Epithelial-Endothelial Crosstalk in Cellular Senescence Driving Clear Cell Renal Cell Carcinoma Malignancy.

Clear cell renal cell carcinoma (ccRCC) is distinguished by the absence of definitive diagnostic mar...

Integrated cross-organ transcriptomic analysis uncovers conserved gene signatures predictive of allograft rejection.

Long-term transplant success is limited by allograft rejection, a complex process traditionally stud...

In-hospital electronic monitoring system approaches to epidemiologic investigation and predictive modeling of contrast-induced acute kidney injury.

Contrast-induced acute kidney injury (CI-AKI), the third most common cause of hospital-acquired kidn...

Self-supervised Deep Learning for Denoising in Ultrasound Microvascular Imaging.

Ultrasound microvascular imaging (UMI) has emerged as a powerful, noninvasive modality for visualizi...

Tracing the evolution of cardiology: Pioneering discoveries and paradigm shifts in cardiovascular care.

Cardiology has undergone an impressive transformation from the initial anatomical observations of Wi...

Retinal imaging and supervised learning predict hospitalizations, kidney, and heart-lung damage in sickle cell disease.

Sickle cell disease (SCD) is a single-gene illness which causes painful vaso-occlusion, debilitating...

Development and validation of a machine learning-based early prediction model for fetal acidosis in vaginal deliveries.

Construction and validation of a glycosylation-related diagnostic model and immune characterization in lupus nephritis.

BACKGROUND: As a critical hallmark of systemic lupus erythematosus, lupus nephritis (LN) stands as a...

A pilot study on the impact of large language model assistance on the evaluation of complex medical living kidney donor candidates.

BACKGROUND: Large language models (LLMs) are undergoing exploration as clinical decision support too...

BA-UNet: A Boundary Augmented Segmentation Network for Cervical Cancer Radiotherapy.

Accurate segmentation of the Clinical Target Volume (CTV) and Organs At Risk (OARs) is a prerequisit...

Concordance Analysis Between KDIGO Definition of Acute Kidney Injury and Its Coding in Clinical Practice.

RATIONALE & OBJECTIVE: Acute kidney injury (AKI) in research is typically identified using KDIGO cri...

Understanding the precipitation mechanism in pentavalent vanadium electrolytes through deep learning potential molecular dynamics.

Vanadium flow batteries (VFBs) represent one of the promising options for large-scale energy storage...

An optimized machine learning approach for reliable design of hybrid FRP-steel-concrete tubular columns.

This study develops and evaluates machine-learning models for predicting the confined ultimate stren...

nnLoGoNet: a hybrid local-global network for retinal vessel segmentation with Skeleton Recall Loss.

Retinal vessel segmentation is a fundamental task in ophthalmic image analysis, playing a critical r...

Predicting primary aldosteronism: risk stratification-based and machine learning-based models.

AIMS: Primary aldosteronism (PA) screening is difficult in an unselected population of hypertensive ...