Nephrology

Predicting Postoperative Stroke in Elderly SICU Patients: An Interpretable Machine Learning Model Using MIMIC Data

Postoperative stroke remains a critical complication in elderly surgical intensive care unit (SICU) patients, contributing to prolonged hospitalization, elevated healthcare costs, and increased mortality. Accurate early risk stratification is essential to enable timely intervention and improve clinical outcomes. We constructed a combined cohort of 19,085 elderly SICU admissions from the MIMIC-II...

Model Systems of Chronic Kidney Disease: A Detailed Overview and Recent Advances.

Experimental model systems, especially animal models, are indispensable tools to study human diseases and to develop new therapeutics. Chronic kidney disease (CKD) is a major global health problem having significantly higher rate of morbidity and mortality. In a pursuit to enhance our understanding of the pathophysiology of CKD and to develop effective treatments, three main model systems, namely ...

Development of Machine-Learning-Based Models for Detection of Cognitive Impairment in Patients Receiving Maintenance Hemodialysis.

BACKGROUND: Cognitive impairment is common but frequently undiagnosed in the dialysis population. We aimed to develop and validate a quick and accurat...

A prognostic model of immunoglobulin A nephropathy using artificial neural network: a retrospective study based on integrated Chinese and Western Medicine.

OBJECTIVE: To establish and evaluate a prognostic model of immunoglobulin A nephropathy (IgAN) based on integrated Chinese and Western Medicine.

Large Language Model-informed ECG Dual Attention Network for Heart Failure Risk Prediction.

Heart failure (HF) poses a significant public health challenge, with a rising global mortality rate. Early detection and prevention of HF could signif...

From planning to prognosis: predicting renal function after minimally-invasive partial nephrectomy with artificial intelligence.

This study presents a machine learning model to predict renal function decline following minimally-invasive partial nephrectomy. Using a dataset of 55...

Vision transformer-based stratification of pre/diabetic and pre/hypertensive patients from retinal photographs for 3PM applications.

OBJECTIVE: Diabetes and hypertension pose significant health risks, especially when poorly managed. Retinal evaluation though fundus photography can p...

Characterization of ROMK cellular heterogeneity along the mouse kidney thick ascending limb.

The renal thick ascending limb (TAL) plays a key role in water and ion homeostasis. Apical potassium secretion via the renal outer medullary potassium...

Explainable machine learning model incorporating social determinants of health to predict chronic kidney disease in type 2 diabetes patients.

BACKGROUND AND OBJECTIVES: Social determinants of health (SDOH) play a critical role in the onset and progression of chronic kidney disease (CKD). Des...

MSMTSeg: Multi-Stained Multi-Tissue Segmentation of Kidney Histology Images via Generative Self-Supervised Meta-Learning Framework.

Accurately diagnosing chronic kidney disease requires pathologists to assess the structure of multiple tissues under different stains, a process that ...

Deep Learning Algorithms to Predict Differential Renal Function <40% in Unilateral Hydronephrosis Based on Key Parameters of Urinary Tract Ultrasound.

OBJECTIVE: To identify the correlation between ultrasound findings and the incidence of differential renal function (DRF) <40%, we conducted an analys...

Machine Learning for Predicting Waitlist Mortality in Pediatric Heart Transplantation.

BACKGROUND: Waitlist mortality remains a critical issue for pediatric heart transplant (HTx) candidates, particularly for candidates with congenital h...

A dynamic model using k-NN algorithm for predicting diabetes and breast cancer.

Healthcare remains a critical focus due to its direct impact on human well-being. Diabetes, currently the fastest-growing chronic disease globally, po...

Predicting long-term patency of radiocephalic arteriovenous fistulas with machine learning and the PREDICT-AVF web app.

The goal of this study was to expand our previously created prediction tool (PREDICT-AVF) and web app by estimating long-term primary and secondary pa...

Identification and validation of inflammatory response genes linking chronic kidney disease with coronary artery disease based on bioinformatics and machine learning.

Coronary artery disease (CAD) commonly occurs and elevates the risk of cardiovascular events and mortality in chronic kidney disease (CKD) patients. T...

Machine Learning Insights Into Amputation Risk: Evaluating Wound Classification Systems in Diabetic Foot Ulcers.

This study compares the performance of various wound classification systems to determine which system most effectively predicts amputation risk in dia...

Comparison of Sarcopenia Assessment in Liver Transplant Recipients by Computed Tomography Freehand Region-of-Interest versus an Automated Deep Learning System.

INTRODUCTION: Sarcopenia, or the loss of muscle quality and quantity, has been associated with poor clinical outcomes in liver transplantation such as...

Artificial intelligence-enhanced interpretation of kidney transplant biopsy: focus on rejection.

PURPOSE OF REVIEW: The objective of this review is to provide an update on the application of artificial intelligence (AI) for the histological interp...

Multi-level feature fusion network for kidney disease detection.

Kidney irregularities pose a significant public health challenge, often leading to severe complications, yet the limited availability of nephrologists...

Establishment of a machine learning-based prediction framework to assess trade-offs in decisions that affect post-HCT outcomes.

In this study, we propose a conceptual framework of decision support tools, built upon machine learning and multi-objective optimization, aimed at off...