AIMC Topic: Glomerular Filtration Rate

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Personalized Prediction of Chronic Kidney Disease Progression in Patients with Chronic Kidney Disease Stages 3-5: A Multicenter Study Using the Machine Learning Approach.

Studies in health technology and informatics
Chronic Kidney Disease (CKD) is a prevalent and progressive condition that can lead to end-stage renal disease (ESRD) if left unmanaged. Accurate prediction of CKD progression, particularly in patients with CKD stages 3-5, is essential for early inte...

The impact of clinical history on the predictive performance of machine learning and deep learning models for renal complications of diabetes.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Diabetes is a chronic disease characterised by a high risk of developing diabetic nephropathy. The early identification of individuals at heightened risk of such complications or their exacerbation can be crucial to set a co...

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

Minerva urology and nephrology
This study presents a machine learning model to predict renal function decline following minimally-invasive partial nephrectomy. Using a dataset of 556 patients treated between 2015 and 2023, the model incorporated patient, tumor, and intraoperative ...

Improved CKD classification based on explainable artificial intelligence with extra trees and BBFS.

Scientific reports
Chronic kidney disease is a persistent ailment marked by the gradual decline of kidney function. Its classification primarily relies on the estimated glomerular filtration rate and the existence of kidney damage. The kidney disease improving global o...

Clinical characteristics, prognosis, and predictive modeling in class IV ± V lupus nephritis.

Frontiers in immunology
OBJECTIVE: The objective of this study is to compare the clinical features and survival outcomes of class IV ± V lupus nephritis (LN) patients, identify risk factors, and develop an accurate prognostic model.

Application of improved glomerular filtration rate estimation by a neural network model in patients with neurogenic lower urinary tract dysfunction.

Clinical nephrology
BACKGROUND: Previous studies have indicated that creatinine (Cr)-based glomerular filtration rate (GFR) estimating equations - including the new Chronic Kidney Disease Epidemiology creatinine (CKD-EPI) equation without race and the estimated glomerul...

Retroperitoneal vs. transperitoneal robotic partial nephrectomy: a multicenter propensity-score matching analysis (PADORA Study - UroCCR n° 68).

Minerva urology and nephrology
BACKGROUND: Robot-assisted partial nephrectomy can be performed through either a transperitoneal or retroperitoneal approach. This study aimed to compare the rate of trifecta achievement between retroperitoneal (RRPN) and transperitoneal (TRPN) robot...

Deep learning automation of MEST-C classification in IgA nephropathy.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
BACKGROUND: Although the MEST-C classification is among the best prognostic tools in immunoglobulin A nephropathy (IgAN), it has a wide interobserver variability between specialized pathologists and others. Therefore we trained and evaluated a tool u...

Influence of Robot-Assisted Partial Nephrectomy on Long-Term Renal Function as Assessed Using 99m-Tc DTPA Renal Scintigraphy.

Journal of endourology
The long-term split renal function after robot-assisted partial nephrectomy (RAPN) is yet to be elucidated. This study aimed to assess long-term renal function of RAPN, using renal scintigraphy, and to identify clinical factors related to deteriorat...