Nephrology

Estimating Residual Native Kidney Urea Clearance in Hemodialysis Patients with and without 24-Hour Urine Volume.

RATIONALE AND OBJECTIVE: Quantification of residual native kidney function (RKF) is rarely performed in patients on hemodialysis. Methods of estimating residual kidney urea clearance (K) that use commonly available laboratory and clinical data, with or without urine volume information, may be useful tools.

Is obesity a contraindication for kidney donation?

INTRODUCTION: To enlarge the donor pool, kidney donors with obesity have been considered. We hypothesized that it is safe for patients with obesity to serve as living kidney donors.

Progression of Metabolic Acidosis in Chronic Kidney Disease.

BACKGROUND: Metabolic acidosis, which is classified into either high anion gap type (high-AGMA) or non-anion gap type (non-AGMA), is a common complica...

Foam Sclerotherapy for Cyst Volume Reduction in Autosomal Dominant Polycystic Kidney Disease: A Prospective Cohort Study.

RATIONALE & OBJECTIVE: Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disorder. Progressive increase in cyst...

Machine Learning Approach for Prediction of Hematic Parameters in Hemodialysis Patients.

This paper shows the application of machine learning techniques to predict hematic parameters using blood visible spectra during ex-vivo treatments. ...

Radiologic-Radiomic Machine Learning Models for Differentiation of Benign and Malignant Solid Renal Masses: Comparison With Expert-Level Radiologists.

The objective of our study was to compare the performance of radiologicradiomic machine learning (ML) models and expert-level radiologists for differ...

Evaluating the performance of a predictive modeling approach to identifying members at high-risk of hospitalization.

To evaluate the risk-of-hospitalization (ROH) models developed at Blue Cross Blue Shield of Louisiana (BCBSLA) and compare this approach to the DxCG ...

Transplant nephrectomy with peritoneal window: Georgetown University experience.

OBJECTIVES: Transplant nephrectomy is a technically challenging procedure with high complication rates. Morbidity and mortality are mostly due to hemo...

Metabolomics meets machine learning: Longitudinal metabolite profiling in serum of normal versus overconditioned cows and pathway analysis.

This study aimed to investigate the differences in the metabolic profiles in serum of dairy cows that were normal or overconditioned when dried off fo...

Minimally invasive nephrectomy for inflammatory renal disease.

OBJECTIVE: Once chronic inflammatory renal disease (IRD) develops, it creates a severe peri-fibrotic process, which makes it a relative contraindicati...

Identification and weighting of kidney allocation criteria: a novel multi-expert fuzzy method.

BACKGROUND: Kidney allocation is a multi-criteria and complex decision-making problem, which should also consider ethical issues in addition to the me...

Deep Learning-Based Histopathologic Assessment of Kidney Tissue.

BACKGROUND: The development of deep neural networks is facilitating more advanced digital analysis of histopathologic images. We trained a convolution...

Profiling of Exosomal Biomarkers for Accurate Cancer Identification: Combining DNA-PAINT with Machine- Learning-Based Classification.

Exosomes are endosome-derived vesicles enriched in body fluids such as urine, blood, and saliva. So far, they have been recognized as potential biomar...

Interventions to Improve Blood Pressure Control Among Socioeconomically Disadvantaged Patients With CKD: Kidney Awareness Registry and Education Pilot Randomized Controlled Trial.

RATIONALE & OBJECTIVE: Sustainable interventions that enhance chronic kidney disease (CKD) management are not often studied in safety-net primary care...

Radiomics of small renal masses on multiphasic CT: accuracy of machine learning-based classification models for the differentiation of renal cell carcinoma and angiomyolipoma without visible fat.

OBJECTIVE: To investigate the discriminative capabilities of different machine learning-based classification models on the differentiation of small (<...

Ameliorative effect of virgin olive oil against nephrotoxicity following sub-chronic administration of ethephon in male rats.

BACKGROUND: Ethephon (EP) is the most famous plant growth regulator with different adverse effects on kidney function. Virgin Olive Oil (VOO) is consi...

Accelerating cardiovascular model building with convolutional neural networks.

The objective of this work is to reduce the user effort required for 2D segmentation when building patient-specific cardiovascular models using the Si...

Pattern recognition and prognostic analysis of longitudinal blood pressure records in hemodialysis treatment based on a convolutional neural network.

OBJECTIVE: The aim of this study is to analyze and visualize blood pressure (BP) patterns during continuous hemodialysis (HD) sessions, referred to as...

Machine learning in predicting graft failure following kidney transplantation: A systematic review of published predictive models.

INTRODUCTION: Machine learning has been increasingly used to develop predictive models to diagnose different disease conditions. The heterogeneity of ...

Artificial Intelligence in Nephrology: Core Concepts, Clinical Applications, and Perspectives.

Artificial intelligence is playing an increasingly important role in many fields of medicine, assisting physicians in most steps of patient management...