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Renal Insufficiency, Chronic

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Automated prognosis of renal function decline in ADPKD patients using deep learning.

Zeitschrift fur medizinische Physik
An accurate prognosis of renal function decline in Autosomal Dominant Polycystic Kidney Disease (ADPKD) is crucial for early intervention. Current biomarkers used are height-adjusted total kidney volume (HtTKV), estimated glomerular filtration rate (...

Clustering-based spatial analysis (CluSA) framework through graph neural network for chronic kidney disease prediction using histopathology images.

Scientific reports
Machine learning applied to digital pathology has been increasingly used to assess kidney function and diagnose the underlying cause of chronic kidney disease (CKD). We developed a novel computational framework, clustering-based spatial analysis (Clu...

Deep Learning Identifies Intelligible Predictors of Poor Prognosis in Chronic Kidney Disease.

IEEE journal of biomedical and health informatics
Early diagnosis and prediction of chronic kidney disease (CKD) progress within a given duration are critical to ensure personalized treatment, which could improve patients' quality of life and prolong survival time. In this study, we explore the inte...

Trends and perspectives for improving quality of chronic kidney disease care: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference.

Kidney international
Chronic kidney disease (CKD) affects over 850 million people globally, and the need to prevent its development and progression is urgent. During the past decade, new perspectives have arisen related to the quality and precision of care for CKD, owing...

Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review.

Journal of nephrology
OBJECTIVES: In this systematic review we aimed at assessing how artificial intelligence (AI), including machine learning (ML) techniques have been deployed to predict, diagnose, and treat chronic kidney disease (CKD). We systematically reviewed the a...

Impact of Warm Ischemia on Acute Kidney Injury After Robotic Partial Nephrectomy Stratified by Baseline Kidney Function.

Journal of endourology
To evaluate the differences in baseline chronic kidney disease (CKD) status in correlations between warm ischemic time (WIT) and acute kidney injury (AKI) or acute/chronic renal function change after robot-assisted partial nephrectomy (RAPN). This ...

A Deep Learning Approach for the Estimation of Glomerular Filtration Rate.

IEEE transactions on nanobioscience
An accurate estimation of glomerular filtration rate (GFR) is clinically crucial for kidney disease diagnosis and predicting the prognosis of chronic kidney disease (CKD). Machine learning methodologies such as deep neural networks provide a potentia...

Machine learning for risk stratification in kidney disease.

Current opinion in nephrology and hypertension
PURPOSE OF REVIEW: Risk stratification for chronic kidney is becoming increasingly important as a clinical tool for both treatment and prevention measures. The goal of this review is to identify how machine learning tools contribute and facilitate ri...