Nephrology

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...

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...

Machine learning-driven prediction model for successful weaning of patients from mechanical ventilation in ICU.

BACKGROUND: Mechanical ventilation is a critical life support technology in the intensive care unit....

A machine learning approach for predicting osmotic coefficients and deriving activity coefficients in alkyl ammonium salts.

Quaternary Ammonium Salts (Quats) have diverse applications across various domains. They are extensi...

Longitudinal Peripheral Blood Transcriptomics Reveal Novel Signatures During Cardiac Allograft Rejection.

BACKGROUND: Acute cellular rejection (ACR) remains a major cause of morbidity after heart transplant...

Acetyl tributyl citrate as a new risk factor for osteoporosis: An integrated study from multi-level toxicological assessment and experimental validation.

This study aimed to elucidate the toxicological effects and underlying mechanisms of the plasticizer...

Validation of histopathology-based deep learning algorithms for detection of actionable non-small cell lung cancer biomarkers.

Non-small cell lung cancer (NSCLC) patient management relies on molecular analysis to determine elig...

Subphenotype Identification for Sepsis-Associated Acute Kidney Injury Using Graph Bidirectional Mamba Networks.

Sepsis-associated acute kidney injury (SA-AKI) is a heterogeneous clinical syndrome and a leading ca...

Adaptive geometric-attention multi-task framework with knowledge distillation for aortic dissection detection in non-contrast CT.

Aortic dissection (AD) is a life-threatening cardiovascular emergency. Non-contrast-enhanced CT (NCE...

Preoperative Neuroimaging Markers, Clinical Severity Measures, and Shunt Characteristics for Predicting Shunt Revision in Idiopathic Intracranial Hypertension: An Explainable Machine-Learning Study.

BACKGROUND AND PURPOSE: Surgical shunt placement is a common treatment for idiopathic intracranial h...