Nephrology

Artificial Intelligence in Cardiovascular Medicine: Focus on Hypertension.

Hypertension remains the most prevalent modifiable risk factor for cardiovascular morbidity and mortality worldwide, yet rates of effective blood pressure control remain persistently suboptimal despite the availability of multiple therapeutic options. This gap reflects fundamental limitations of current care models, which rely on episodic measurements, population-based treatment algorithms, and in...

Cardiovascular outcomes and subclinical atherosclerosis in metabolic-associated steatotic liver disease: long-term follow-up from a specialized outpatient cohort.

BACKGROUND AND AIMS: Cardiovascular disease is the main cause of mortality in metabolic-associated steatotic liver disease (MASLD). This study evaluated both observed and predicted cardiovascular outcomes using the Framingham risk score in a MASLD cohort and assessed subclinical atherosclerosis via carotid and femoral Doppler, along with its correlates at follow-up. METHODS: Retrospective cohort i...

Machine-learning approach on echocardiography to improve the detection of transthyretin amyloid cardiomyopathy: GRAAL algorithm.

AIMS: Transthyretin amyloid cardiomyopathy (ATTR-CM) is an increasingly recognized cause of heart failure, yet detection remains challenging due to it...

Clinical prediction of the mortality for acute kidney injury in decompensated cirrhosis.

Acute kidney injury (AKI) is a severe complication in patients with decompensated cirrhosis, associated with increased mortality. This study aimed to ...

Explainable machine learning for long-term cardiovascular disease risk prediction in Chinese middle-aged and older adults: a 9-year longitudinal cohort study with web-based risk calculator.

Cardiovascular disease represents the leading cause of mortality in China, accounting for over 40% of all deaths. Existing risk prediction models pred...

In-silico study of machine learning discovers de novo lipogenesis for predicting prognosis and immunotherapy responses in kidney renal clear cell carcinoma.

Prediction of graft outcomes after kidney transplantation: When standard statistics compare to machine learning techniques.

BACKGROUND: Over the last decade, the use of machine learning (ML) techniques in problem modeling and solving has increased significantly, including i...

Diet-microbiota-kidney axis reprogramming: mechanistic insights into microbial metabolite-driven precision nutrition for chronic kidney disease.

Medical nutrition therapy serves as the cornerstone in the management of chronic kidney disease (CKD). While conventional approaches emphasize macronu...

Metagenomic profiling and predictive modeling of the gut microbiome reveal signatures of gestational disease.

The gut microbiome plays a vital role in maternal health and pregnancy outcomes, yet its impact on conditions like gestational hypertension (GH) and g...

Personalized prediction of initial valproic acid dose in children with epilepsy using machine learning techniques.

INTRODUCTION: Valproic acid (VPA) is widely prescribed antiepileptic drug in children because of its broad-spectrum efficacy. However, marked inter-in...

Evaluation of explainable machine learning models for predicting mid-term stone recurrence after percutaneous nephrolithotomy: a retrospective observational cohort study.

OBJECTIVE: To develop an explainable machine learning (ML) model to predict mid-term (3 years) stone recurrence (SR) after percutaneous nephrolithotom...

Transformer-based deep learning model for real-time prediction of intraoperative hypotension using dynamic time-series vital signs: A retrospective study.

BACKGROUND: The clinical importance of transient intraoperative hypotension (IOH) remains debated, and existing models often rely on high-resolution w...

International Delphi consensus on acute kidney injury: Foundations for AI-driven digital twin development in critical care nephrology.

BACKGROUND: Acute kidney injury (AKI) in critically ill patients is clinically complex and heterogeneous, limiting the development of structured simul...

Large-scale plasma proteomics for predicting future cardiovascular and all-cause mortality among individuals with cardiovascular-kidney-metabolic syndrome stage 0-3.

BACKGROUND: Identifying high-risk individuals for cardiovascular and all-cause mortality among individuals with cardiovascular-kidney-metabolic (CKM) ...

Recent advances in low-temperature ceramic fuel cells: material design and applications.

Ceramic fuel cells (CFCs) are highly efficient and clean electrochemical energy conversion devices, featuring a wide range of available fuels (hydroge...

2D Multimodal Image Collection for Fluorescence Prediction from Transmitted Light Microscopy.

We present the Light My Cells Database, a large-scale open-access collection comprising 2,574 acquisition sets and 56,984 microscopy 2D images designe...

Integrated single-cell and bulk transcriptomic analysis identifies epithelial cell-related biomarkers and immune subtypes in focal segmental glomerulosclerosis.

BACKGROUND: Focal segmental glomerulosclerosis (FSGS) is a major cause of nephrotic syndrome and chronic kidney disease, characterized by podocyte inj...

Severe COVID-19 in the Republic of Korea: Epidemiology, Risk Factors, Therapeutics, and Prognostic Models From Nationwide Data.

Severe coronavirus disease 2019 (COVID-19) has posed ongoing clinical and public health challenges worldwide, with Korea providing a unique perspectiv...

Exploring Deep Learning Models for Small Histopathology Datasets: Segmentation and Classification of Glomerular Crescent Lesions with Ablation, Interpretability, and Calibration Analyses.

Glomerular crescent lesions are critical indicators of severe kidney injury and are closely associated with disease progression. However, their automa...

Cardiopulmonary exercise testing in contemporary cardiology: physiological insights, novel applications and evolving algorithms.

Cardiopulmonary exercise testing (CPET) allows for the study of the pathophysiology of exercise intolerance through assessment of exercise integrative...