Nephrology

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...

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 ...

Interpretable machine learning model for predicting refeeding syndrome after colorectal cancer surgery.

OBJECTIVE: Refeeding syndrome (RFS) is a common yet frequently overlooked complication during postop...

PHLDB1 and WDFY4 as dual-state biomarkers in SLE pathogenesis and lupus nephritis prediction.

OBJECTIVES: Our previous study confirmed systemic lupus erythematosus (SLE) associated with polymorp...

Predicting kidney graft survival with a machine learning model based on for-cause biopsy transcriptomics.

Kidney transplantation significantly improves outcomes in end-stage renal disease, however, long-ter...

Diagnostic Accuracy of Artificial Intelligence-Enabled Retinal Biomarkers for Detecting Type 2 Diabetes and Prediabetes Among Asian Indians [DART Study].

PURPOSE: To identify retinal microvascular features that distinguish normoglycemia from diabetes mel...

Prediction of renal cell carcinoma: Development and validation of machine learning model.

Renal cell carcinoma (RCC) is the leading cause of urinary system morbidity and mortality. Early ide...

An exploratory study on the relationship between renal cell carcinoma and CAFs infiltration by integrating Pathomics and collagen features.

OBJECTIVE: Cancer-associated fibroblasts (CAFs) are a critical component of the tumor microenvironme...

Coriandrum sativum improves prognosis in clear cell renal cell carcinoma by targeting NEK6 to modulate the immune microenvironment: a predictive study based on network pharmacology and multi-omics analysis.

Coriandrum sativum L. (coriander) is a medicinal herb with diverse pharmacological properties, but i...

Chronic kidney disease detection using XceptionNet with Harmonic Addax Optimization.

Chronic Kidney Disease (CKD) refers to a persistent and progressive impairment of kidney function oc...

Comment on Machine learning survival analysis for predicting kidney disease progression in patients with acute kidney injury undergoing continuous kidney replacement therapy: An analysis of the LINKA database.

Exploration Novel Therapeutic Targets for Periodontitis via Stress Granules Biomarkers.

BACKGROUND: Periodontitis (PD) is associated with stress granules (SGs), which are involved in cellu...

Characterizing prognostic and immunological traits of kidney renal clear cell carcinoma via mitochondria-associated membranes and identifying DNM1L as a potential therapeutic target using machine learning.

MYO1C is a urinary extracellular vesicle biomarker and mediator of podocyte injury in diabetic nephropathy.

Type 2 diabetic nephropathy (T2DN) is a major complication of type 2 diabetes and a leading cause of...

How do chronic diseases affect personal and household income? A double debiased machine learning analysis of the China health and retirement longitudinal study (CHARLS) in older adults.

OBJECTIVES: This study aimed to investigate the impacts of chronic diseases such as hypertension, dy...

The discordance of remnant cholesterol and low-density lipoprotein cholesterol as a predictor of diabetes, diabetic microvascular diseases, and cardiovascular disease.

BACKGROUND: The impact of discordance between remnant cholesterol (RC) and low-density lipoprotein c...

Numerical modeling and prediction of late estimated glomerular filtration rate in kidney transplant recipients based on machine learning models and the Monte Carlo simulation method.

OBJECTIVES: This paper presents an experimental numerical method for modeling and analyzing stochast...