AIMC Topic: Glomerular Filtration Rate

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A nomogram for predicting renal function recovery after robotic-assisted ureteral reconstruction: development and comparative validation using traditional and machine learning models.

Journal of robotic surgery
OBJECTIVE: To develop, validate, and compare a Traditional Multivariable Logistic Regression model with a Machine Learning-based LASSO Regression Model for predicting significant renal function recovery in adult patients undergoing surgical repair fo...

Prediction of advanced chronic kidney disease through retinal fundus images by deep learning.

Scientific reports
This study was developed and evaluated deep learning model for detecting chronic kidney disease (CKD) by retinal fundus images. This study included 42,963 clinical visits from 17,442 patients who underwent retinal fundus examination between October 1...

Exploring the potential relationship between kidney disease index and cognitive dysfunction: a machine learning approach with NHANES data.

BMC geriatrics
OBJECTIVE: This study investigates the relationship between the Kidney Disease Index (KDI) and cognitive function, evaluating its potential as a predictive marker for cognitive impairment in older adults. We also compare the performance of KDI with t...

Personalized prediction model generated with machine learning for kidney function one year after living kidney donation.

Scientific reports
Living kidney donors typically experience approximately a 30% reduction in kidney function after donation, although the degree of reduction varies among individuals. This study aimed to develop a machine learning (ML) model to predict serum creatinin...

Predicting rapid kidney function decline in middle-aged and elderly Chinese adults using machine learning techniques.

BMC medical informatics and decision making
The rapid decline of kidney function in middle-aged and elderly people has become an increasingly serious public health problem. Machine learning (ML) technology has substantial potential to disease prediction. The present study use dataset from the ...

Developing a CT radiomics-based model for assessing split renal function using machine learning.

Japanese journal of radiology
PURPOSE: This study aims to investigate whether non-contrast computed tomography radiomics can effectively reflect split renal function and to develop a radiomics model for its assessment.

A neural network approach to glomerular filtration rate estimation: a single-centre retrospective audit.

Nuclear medicine communications
OBJECTIVES: The 2009 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation without race correction factor is frequently used for an estimate of glomerular filtration rate (eGFR) and to support a single-sample GFR regime. This study exa...

Determining IFI44 as a key lupus nephritis's biomarker through bioinformatics and immunohistochemistry.

Renal failure
BACKGROUND: Lupus nephritis (LN) emerges as a severe complication of systemic lupus erythematosus (SLE), significantly affecting patient survival. Despite improvements in treatment reducing LN's morbidity and mortality, existing therapies remain subo...