Nephrology

Control of hyperparathyroidism with the intravenous calcimimetic etelcalcetide in dialysis patients adherent and non-adherent to oral calcimimetics.

BACKGROUND: In dialysis patients, non-adherence to oral cinacalcet adds complexity to the control of secondary hyperparathyroidism. The present study aims to evaluate the use of intravenous calcimimetic, etelcalcetide, in the control of secondary hyperparathyroidism in patients adherent and non-adherent to oral calcimimetics.

Automated differentiation of benign renal oncocytoma and chromophobe renal cell carcinoma on computed tomography using deep learning.

OBJECTIVES: To develop and evaluate the feasibility of an objective method using artificial intelligence (AI) and image processing in a semi-automated fashion for tumour-to-cortex peak early-phase enhancement ratio (PEER) in order to differentiate CD117(+) oncocytoma from the chromophobe subtype of renal cell carcinoma (ChRCC) using convolutional neural networks (CNNs) on computed tomography imagi...

Comparison Studies of "Ultrathin Parenchyma" Resection and Sharp Dissection in Robotic Partial Nephrectomy for Renal Tumors.

The aim of this study was to introduce the "ultrathin parenchyma" resection in a robot-assisted partial nephrectomy (RAPN) via the retroperitoneal ap...

Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy.

BACKGROUND: Previous scoring models such as the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) and the Sequential Organ Fai...

Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone.

BACKGROUND: Cardiovascular diseases kill approximately 17 million people globally every year, and they mainly exhibit as myocardial infarctions and he...

PiNN: A Python Library for Building Atomic Neural Networks of Molecules and Materials.

Atomic neural networks (ANNs) constitute a class of machine learning methods for predicting potential energy surfaces and physicochemical properties o...

A Super-Lightweight and Soft Manipulator Driven by Dielectric Elastomers.

Some applications are very sensitive to the weight of the robot, such as space manipulation or any untethered mobile manipulation. In this article, we...

Classification of glomerular hypercellularity using convolutional features and support vector machine.

Glomeruli are histological structures of the kidney cortex formed by interwoven blood capillaries, and are responsible for blood filtration. Glomerula...

Investigating the use of data-driven artificial intelligence in computerised decision support systems for health and social care: A systematic review.

There is growing interest in the potential of artificial intelligence to support decision-making in health and social care settings. There is, however...

First-in-human evaluation of a hand-held automated venipuncture device for rapid venous blood draws.

Obtaining venous access for blood sampling or intravenous (IV) fluid delivery is an essential first step in patient care. However, success rates rely ...

Machine learning with autophagy-related proteins for discriminating renal cell carcinoma subtypes.

Machine learning techniques have been previously applied for classification of tumors based largely on morphological features of tumor cells recognize...

Upstaging to pT3a disease in patients undergoing robotic partial nephrectomy for cT1 kidney cancer: Outcomes and predictors from a multi-institutional dataset.

OBJECTIVES: Surgically treated clinical T1 (cT1) kidney cancer has in general a good prognosis, but there is a risk of upstaging that can potentially ...

Active learning for accuracy enhancement of semantic segmentation with CNN-corrected label curations: Evaluation on kidney segmentation in abdominal CT.

Segmentation is fundamental to medical image analysis. Recent advances in fully convolutional networks has enabled automatic segmentation; however, hi...

Improved small blob detection in 3D images using jointly constrained deep learning and Hessian analysis.

Imaging biomarkers are being rapidly developed for early diagnosis and staging of disease. The development of these biomarkers requires advances in bo...

Deep Learning to Distinguish Benign from Malignant Renal Lesions Based on Routine MR Imaging.

PURPOSE: With increasing incidence of renal mass, it is important to make a pretreatment differentiation between benign renal mass and malignant tumor...

Early Recognition of Burn- and Trauma-Related Acute Kidney Injury: A Pilot Comparison of Machine Learning Techniques.

Severely burned and non-burned trauma patients are at risk for acute kidney injury (AKI). The study objective was to assess the theoretical performanc...

Dynamic coronary roadmapping via catheter tip tracking in X-ray fluoroscopy with deep learning based Bayesian filtering.

Percutaneous coronary intervention (PCI) is typically performed with image guidance using X-ray angiograms in which coronary arteries are opacified wi...

Differentiation of Small (≤ 4 cm) Renal Masses on Multiphase Contrast-Enhanced CT by Deep Learning.

This study evaluated the utility of a deep learning method for determining whether a small (≤ 4 cm) solid renal mass was benign or malignant on multi...

Training and Validation of Deep Neural Networks for the Prediction of 90-Day Post-Liver Transplant Mortality Using UNOS Registry Data.

Prediction models of post-liver transplant mortality are crucial so that donor organs are not allocated to recipients with unreasonably high probabili...

Membranous Nephropathy with Rapid Progression.

We report a 49-year-old man with microscopic hematuria, subnephrotic proteinuria, and rapidly progressive renal failure. His biopsy had features of Ph...