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Creatinine

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Estimation of Baseline Serum Creatinine with Machine Learning.

American journal of nephrology
INTRODUCTION: Comparing current to baseline serum creatinine is important in detecting acute kidney injury. In this study, we report a regression-based machine learning model to predict baseline serum creatinine.

A novel approach to dry weight adjustments for dialysis patients using machine learning.

PloS one
BACKGROUND AND AIMS: Knowledge of the proper dry weight plays a critical role in the efficiency of dialysis and the survival of hemodialysis patients. Recently, bioimpedance spectroscopy(BIS) has been widely used for set dry weight in hemodialysis pa...

Prediction of vancomycin dose on high-dimensional data using machine learning techniques.

Expert review of clinical pharmacology
OBJECTIVES: Despite therapeutic vancomycin is regularly monitored, its dose requirements vary considerably between individuals. Various innovative vancomycin dosing strategies have been developed for dose optimization; however, the utilization of ind...

Comparison of plasma neutrophil gelatinase-associated lipocalin (NGAL) levels after robot-assisted laparoscopic and retropubic radical prostatectomy: an observational study.

Brazilian journal of anesthesiology (Elsevier)
BACKGROUND AND OBJECTIVES: Patients undergoing radical prostatectomy are at increased risk of Acute Kidney Injury (AKI) because of intraoperative bleeding, obstructive uropathy, and older age. Neutrophil Gelatinase-Associated Lipocalin (NGAL) may bec...

Comparison of machine learning and logistic regression models in predicting acute kidney injury: A systematic review and meta-analysis.

International journal of medical informatics
INTRODUCTION: We aimed to assess whether machine learning models are superior at predicting acute kidney injury (AKI) compared to logistic regression (LR), a conventional prediction model.

A Deep Learning Program to Predict Acute Kidney Injury.

Studies in health technology and informatics
Acute kidney injury is a dangerous and sometime fatal clinical situation, which can cause irreversible damage. If we can predict it earlier and make appropriate prevention before its outbreak, kidney injury could be avoided. One challenge of early re...

Robotic versus hand-assisted laparoscopic living donor nephrectomy: comparison of two minimally invasive techniques in kidney transplantation.

Journal of robotic surgery
Robot-assisted donor nephrectomy (RDN) is increasingly used due to its advantages such as its precision and reduced learning curve when compared to laparoscopic techniques. Concerns remain among surgeons regarding possible longer warm ischemia time. ...

A Deep Learning Approach for the Estimation of Glomerular Filtration Rate.

IEEE transactions on nanobioscience
An accurate estimation of glomerular filtration rate (GFR) is clinically crucial for kidney disease diagnosis and predicting the prognosis of chronic kidney disease (CKD). Machine learning methodologies such as deep neural networks provide a potentia...

End-to-end interstitial fibrosis assessment of kidney biopsies with a machine learning-based model.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
BACKGROUND: The extent of interstitial fibrosis in the kidney not only correlates with renal function at the time of biopsy but also predicts future renal outcome. However, its assessment by pathologists lacks good agreement. The aim of this study is...