Nephrology

Prediction model development of late-onset preeclampsia using machine learning-based methods.

Preeclampsia is one of the leading causes of maternal and fetal morbidity and mortality. Due to the lack of effective preventive measures, its prediction is essential to its prompt management. This study aimed to develop models using machine learning to predict late-onset preeclampsia using hospital electronic medical record data. The performance of the machine learning based models and models usi...

A non-linear mathematical model using optical sensor to predict heart decellularization efficacy.

One of the main problems of the decellularization technique is the subjectivity of the final evaluation of its efficacy in individual organs. This problem can result in restricted cell repopulation reproducibility and worse responses to transplant tissues. Our proposal is to analyze the optical profiles produced by hearts during perfusion decellularization, as an additional method for evaluating t...

Precise estimation of renal vascular dominant regions using spatially aware fully convolutional networks, tensor-cut and Voronoi diagrams.

This paper presents a new approach for precisely estimating the renal vascular dominant region using a Voronoi diagram. To provide computer-assisted d...

A self-supervised strategy for fully automatic segmentation of renal dynamic contrast-enhanced magnetic resonance images.

PURPOSE: An automated accurate segmentation for dynamic contrast-enhanced magnetic resonance (DCE-MR) image sequences is essential for quantification ...

Machine learning versus physicians' prediction of acute kidney injury in critically ill adults: a prospective evaluation of the AKIpredictor.

BACKGROUND: Early diagnosis of acute kidney injury (AKI) is a major challenge in the intensive care unit (ICU). The AKIpredictor is a set of machine-l...

Artificial intelligence predicts the progression of diabetic kidney disease using big data machine learning.

Artificial intelligence (AI) is expected to support clinical judgement in medicine. We constructed a new predictive model for diabetic kidney diseases...

Machine learning analysis of serum biomarkers for cardiovascular risk assessment in chronic kidney disease.

BACKGROUND: Chronic kidney disease (CKD) patients show an increased burden of atherosclerosis and high risk of cardiovascular events (CVEs). There are...

Machine Learning Classification for Assessing the Degree of Stenosis and Blood Flow Volume at Arteriovenous Fistulas of Hemodialysis Patients Using a New Photoplethysmography Sensor Device.

The classifier of support vector machine (SVM) learning for assessing the quality of arteriovenous fistulae (AVFs) in hemodialysis (HD) patients using...

Anemia and iron deficiency among chronic kidney disease Stages 3-5ND patients in the Chronic Kidney Disease Outcomes and Practice Patterns Study: often unmeasured, variably treated.

BACKGROUND: International variation in anemia assessment and management practices in chronic kidney disease (CKD) is poorly understood.

On the interpretability of machine learning-based model for predicting hypertension.

BACKGROUND: Although complex machine learning models are commonly outperforming the traditional simple interpretable models, clinicians find it hard t...

Validation of a simple equation for glomerular filtration rate measurement based on plasma iohexol disappearance.

BACKGROUND: A simple equation for glomerular filtration rate (GFR) measurement based on only plasma samples during the slow compartment after injectio...

Microwave dielectric property based classification of renal calculi: Application of a kNN algorithm.

The proper management of renal lithiasis presents a challenge, with the recurrence rate of the disease being as high as 46%. To prevent recurrence, th...

Predicting ideal outcome after pediatric liver transplantation: An exploratory study using machine learning analyses to leverage Studies of Pediatric Liver Transplantation Data.

Machine learning analyses allow for the consideration of numerous variables in order to accommodate complex relationships that would not otherwise be ...

An artificial intelligence-based clinical decision support system for large kidney stone treatment.

A decision support system (DSS) was developed to predict postoperative outcome of a kidney stone treatment procedure, particularly percutaneous nephro...

Pan-Renal Cell Carcinoma classification and survival prediction from histopathology images using deep learning.

Histopathological images contain morphological markers of disease progression that have diagnostic and predictive values. In this study, we demonstrat...

Screening and Bioinformatics Analysis of IgA Nephropathy Gene Based on GEO Databases.

PURPOSE: To identify novel biomarkers of IgA nephropathy (IgAN) through bioinformatics analysis and elucidate the possible molecular mechanism.

High-Resolution SPECT Imaging of Stimuli-Responsive Soft Microrobots.

Untethered small-scale robots have great potential for biomedical applications. However, critical barriers to effective translation of these miniaturi...

Prediction of Aneurysm Stability Using a Machine Learning Model Based on PyRadiomics-Derived Morphological Features.

Background and Purpose- Discrimination of the stability of intracranial aneurysms is critical for determining the treatment strategy, especially in sm...

BP-ANN Model Coupled with Particle Swarm Optimization for the Efficient Prediction of 2-Chlorophenol Removal in an Electro-Oxidation System.

Electro-oxidation is an effective approach for the removal of 2-chlorophenol from wastewater. The modeling of the electrochemical process plays an imp...

An integrated model using the Taguchi method and artificial neural network to improve artificial kidney solidification parameters.

BACKGROUND: Hemodialysis mainly relies on the "artificial kidney," which plays a very important role in temporarily or permanently substituting for th...