Nephrology

Plasma signals of lung tumor promotion for molecular cancer prevention.

Predicting lung cancer risk would enhance prevention trials. Although the Canakinumab Anti-inflammatory Thrombosis Outcome Study (CANTOS) trial demonstrated reduced lung cancer incidence with interleukin (IL)-1β inhibition, the high number needed to treat (NNT) to prevent lung cancer limits its use in unselected populations. Using machine learning, we identified a 14-protein plasma signature predi...

CT-based deep learning radiogenomics for predicting key glioma genotypes (IDH, ATRX, EGFR, TP53).

PURPOSE: Molecular subtyping guides diagnosis and targeted therapy for gliomas. Although MRI-the current imaging standard-can be time-consuming and is sometimes contraindicated, computed tomography (CT) is faster, more widely available, and often preferable in emergency and resource-limited settings. We evaluated whether CT-based radiogenomic signatures combined with machine learning could accurat...

A systematic review of machine learning algorithms for mortality risk, readmission and phenotype prediction in patients with heart failure: exploring key data sources, input variables and outcomes.

BACKGROUND: Heart failure is not only a prevalent disease with a high mortality rate, but also generates high costs for healthcare systems. By trainin...

Single-cell-based analysis establishes C1QA-mediated promotion of high glucose-induced tubular epithelial injury via ERS in DN.

BACKGROUND: Diabetic nephropathy (DN) poses a growing worldwide health challenge as a leading cause of end-stage renal disease, a condition that arise...

Machine Learning-Assisted KCl-CaCl2-LiCl Electrolyte Design for Low-Temperature, High-Performance Calcium-Based Liquid Metal Batteries.

Calcium-based liquid metal batteries are promising for large-scale energy storage due to calcium abundance and low cost, yet their practical applicati...

Development and validation of a machine learning-based clinical decision support tool for stratifying intravenous medication risk in hospitalized patients with heart failure.

INTRODUCTION: Hospitalized patients with heart failure (HF) frequently receive multiple high-risk intravenous (IV) medications, placing them at a subs...

Comparative effectiveness and cost-effectiveness of an artificial intelligence workflow for small renal mass diagnosis on computed tomography.

INTRODUCTION: Small renal masses are increasingly detected on imaging, but their accurate classification as benign, indolent, or aggressive remains ch...

Clinical Evaluation of the Clinical Reasoning Process of Large Language Models in Nephrology: Comparative Evaluation Study.

This study evaluates the dynamic clinical reasoning of 4 leading large language models in complex nephrology cases, demonstrating that while Gemini 2....

Advances in the diagnosis and detection of chronic kidney disease.

Chronic kidney disease affects 788-844 million adults worldwide and is projected to become the fifth leading cause of death by 2040. Global burden est...

Cytoreductive nephrectomy improves survival in metastatic papillary renal cell carcinoma: a population-based study with machine learning validation and landmark analysis.

BACKGROUND: The role of cytoreductive nephrectomy (CN) in metastatic papillary renal cell carcinoma (pRCC) remains poorly defined, as most CN evidence...

Happiness and hypertension prevalence: A global analysis.

The prevalence of hypertension around the world is high while hypertension control is relatively low. The objective of this study is to investigate th...

Endothelial activation and stress index associated with in-hospital mortality risk in patients with end-stage renal disease: a retrospective analysis based on the MIMIC database and machine learning model development.

BACKGROUND: End-stage renal disease (ESRD) is a severe chronic renal disorder with high mortality, requiring dialysis treatment or kidney transplantat...

Ultrasound elastography in pediatric care: bridging innovation and noninvasive diagnostics.

This review explores the application and limitations of ultrasound elastography (USE) in the pediatric population, addressing its diagnostic value acr...

High-quality dietary patterns reduce risk of advanced cardiovascular-kidney-metabolic syndrome: A cross-sectional NHANES study in US adults.

Evidence-based dietary strategies for mitigating Cardiovascular-kidney-metabolic (CKM) syndrome progression remain limited; therefore, we hypothesized...

Development and temporal external validation of a high-specificity XGBoost rule-in model for diabetes in middle-aged and older Korean adults.

Early identification of diabetes in older adults is essential for preventing complications, yet many high‑risk individuals remain undetected in commun...

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 ...

Precision Medicine Gene Network Analyser: part I-cancer driver gene identification through network topology and ensemble machine learning.

PURPOSE: Precision oncology depends on identifying cancer driver genes and linking them to targeted therapies. Current methods using curated gene sets...

Advances in biosensors for monitoring immune responses and allograft rejection in organ transplantation.

Organ transplantation remains a gold-standard intervention for numerous end-stage organ failure diseases. However, allograft rejection is still a barr...

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...

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...