Nephrology

Predicting osteoporosis from kidney-ureter-bladder radiographs utilizing deep convolutional neural networks.

Osteoporosis is a common condition that can lead to fractures, mobility issues, and death. Although ...

Predicting clinical outcomes of SARS-CoV-2 infection during the Omicron wave using machine learning.

The Omicron SARS-CoV-2 variant continues to strain healthcare systems. Developing tools that facilit...

A systematic review of prediction models on arteriovenous fistula: Risk scores and machine learning approaches.

OBJECTIVE: Failure-to-mature and early stenosis remains the Achille's heel of hemodialysis arteriove...

An explainable machine learning model to predict early and late acute kidney injury after major hepatectomy.

BACKGROUND: Risk assessment models for acute kidney injury (AKI) after major hepatectomy that differ...

Application of interpretable machine learning algorithms to predict acute kidney injury in patients with cerebral infarction in ICU.

BACKGROUND: Acute kidney injury (AKI) is not only a complication but also a serious threat to patien...

Comment on Enhanced Artificial Intelligence Strategies in Renal Oncology: Iterative Optimization and Comparative Analysis of GPT 3.5 Versus 4.0.

Predictive modeling of co-infection in lupus nephritis using multiple machine learning algorithms.

This study aimed to analyze peripheral blood lymphocyte subsets in lupus nephritis (LN) patients and...

Generalizing the application of machine learning predictive models across different populations: does a model to predict the use of renal replacement therapy in critically ill COVID-19 patients apply to general intensive care unit patients?

Effects of tacrolimus on proteinuria in Chinese and Indian patients with idiopathic membranous nephropathy: the results of machine learning study.

PURPOSE: The present study aims to explore the effects of tacrolimus on proteinuria in patients with...

Machine learning algorithms to predict colistin-induced nephrotoxicity from electronic health records in patients with multidrug-resistant Gram-negative infection.

OBJECTIVES: Colistin-induced nephrotoxicity prolongs hospitalisation and increases mortality. The st...

Development of Novel Methods for QSAR Modeling by Machine Learning Repeatedly: A Case Study on Drug Distribution to Each Tissue.

Artificial intelligence is expected to help identify excellent candidates in drug discovery. However...

Deep learning prediction of renal anomalies for prenatal ultrasound diagnosis.

Deep learning algorithms have demonstrated remarkable potential in clinical diagnostics, particularl...

Renal artery pseudoaneurysm following robot assisted nephron sparing surgery: two case reports.

BACKGROUND: Renal artery pseudoaneurysm following partial nephrectomy is a rare entity, the incidenc...

Deep-learning model for evaluating histopathology of acute renal tubular injury.

Tubular injury is the most common cause of acute kidney injury. Histopathological diagnosis may help...

Radiomics and machine learning for renal tumor subtype assessment using multiphase computed tomography in a multicenter setting.

OBJECTIVES: To distinguish histological subtypes of renal tumors using radiomic features and machine...

Reproducibility and prognostic ability of chronicity parameters in kidney biopsy - Comprehensive evaluation comparing microscopy and artificial intelligence in digital pathology.

INTRODUCTION: Semi-quantitative scoring of various parameters in renal biopsy is accepted as an impo...

UroAngel: a single-kidney function prediction system based on computed tomography urography using deep learning.

BACKGROUND: Accurate estimation of the glomerular filtration rate (GFR) is clinically crucial for de...

Assessing the perioperative outcomes of abdominal drain omission after robot-assisted partial nephrectomy.

The study aimed to evaluate the impact of abdominal drain placement (vs. omission) on perioperative ...

Text mining of hypertension researches in the west Asia region: a 12-year trend analysis.

More than half of the world population lives in Asia and hypertension (HTN) is the most prevalent ri...

The application of different machine learning models based on PET/CT images and EGFR in predicting brain metastasis of adenocarcinoma of the lung.

OBJECTIVE: To explore the value of six machine learning models based on PET/CT radiomics combined wi...

[Artificial intelligence in kidney transplant pathology].

BACKGROUND: Artificial intelligence (AI) systems have showed promising results in digital pathology,...