Nephrology

Will deep learning change outcomes in liver transplant?

One-Step Robot-Assisted Complete Urinary Tract Extirpation in Man with End-Stage Renal Disease on Dialysis: The First Case Report.

Urothelial carcinoma (UC) could be observed in urinary bladder (UBUC) and upper urinary tracts (UTUC...

Combating hypertension beyond genome-wide association studies: Microbiome and artificial intelligence as opportunities for precision medicine.

The single largest contributor to human mortality is cardiovascular disease, the top risk factor for...

Application of robotics in abdominal organ transplantation: A bibliometric analysis.

BACKGROUND: Robotic transplant surgery has garnered worldwide attention since 2002. Discussions on t...

Machine-learning predictive model of pregnancy-induced hypertension in the first trimester.

In the first trimester of pregnancy, accurately predicting the occurrence of pregnancy-induced hyper...

A hybrid approach to full-scale reconstruction of renal arterial network.

The renal vasculature, acting as a resource distribution network, plays an important role in both th...

Deep learning-based multi-model approach on electron microscopy image of renal biopsy classification.

BACKGROUND: Electron microscopy is important in the diagnosis of renal disease. For immune-mediated ...

Impact of tumor contact surface area on collecting system entry in robot-assisted partial nephrectomy: a retrospective analysis.

BACKGROUND: Collecting system entry in robot-assisted partial nephrectomy may occur even in cases sh...

Muscle magnetic resonance characterization of STIM1 tubular aggregate myopathy using unsupervised learning.

PURPOSE: Congenital myopathies are a heterogeneous group of diseases affecting the skeletal muscles ...

Effective deep learning classification for kidney stone using axial computed tomography (CT) images.

INTRODUCTION: Stone formation in the kidneys is a common disease, and the high rate of recurrence an...

Survey and Evaluation of Hypertension Machine Learning Research.

Background Machine learning (ML) is pervasive in all fields of research, from automating tasks to co...

Long term experience of robotic retroperitoneal partial nephrectomy as the default approach in the management of renal masses: should the paradigm shift?

Although retroperitoneal surgery has demonstrated a better quality of recovery compared to transperi...

Preliminary evaluation of deep learning for first-line diagnostic prediction of tumor mutational status.

The detection of tumour gene mutations by DNA or RNA sequencing is crucial for the prescription of e...

Body composition predicts hypertension using machine learning methods: a cohort study.

We used machine learning methods to investigate if body composition indices predict hypertension. Da...

First Comparison of Retroperitoneal Versus Transperitoneal Robot-Assisted Nephroureterectomy with Bladder Cuff: A Single Center Study.

INTRODUCTION: After recent presentation of the first complete robot-assisted retroperitoneal nephrou...

Differential diagnosis of secondary hypertension based on deep learning.

Secondary hypertension is associated with higher risks of target organ damage and cardiovascular and...

High-throughput image analysis with deep learning captures heterogeneity and spatial relationships after kidney injury.

Recovery from acute kidney injury can vary widely in patients and in animal models. Immunofluorescen...

Relating process and outcome metrics for meaningful and interpretable cannulation skill assessment: A machine learning paradigm.

BACKGROUND AND OBJECTIVES: The quality of healthcare delivery depends directly on the skills of clin...

Nonparametric failure time: Time-to-event machine learning with heteroskedastic Bayesian additive regression trees and low information omnibus Dirichlet process mixtures.

Many popular survival models rely on restrictive parametric, or semiparametric, assumptions that cou...

Assessing the Effects of Deep Learning Reconstruction on Abdominal CT Without Arm Elevation.

To evaluate the effects of deep learning reconstruction (DLR) on image quality of abdominal compute...

A novel multiplex score to predict outcomes of partial nephrectomy for multiple tumors.

BACKGROUND: The RENAL nephrometry score (RNS) is widely used to describe renal mass complexity and i...