Nephrology

Latest AI and machine learning research in nephrology for healthcare professionals.

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Interpretable machine learning-based insights into early-life endocrine disruptor exposure and small vulnerable newborns.

Early-life exposure to endocrine-disrupting chemicals (EDCs) may contribute to small vulnerable newb...

Microscope-Assisted Hypertensive Retinopathy Diagnosis Using Deep Learning Models.

The retina is the most crucial part of the human eye, and it can be affected due to hypertension. Ho...

Foundation Model and Radiomics-Based Quantitative Characterization of Perirenal Fat in Renal Cell Carcinoma Surgery.

RATIONALE AND OBJECTIVES: To quantitatively characterize the degree of perirenal fat adhesion using ...

A new era in nephrology: the role of super-resolution microscopy in research, medical diagnostic, and drug discovery.

For decades, electron microscopy has been the primary method to visualize ultrastructural details of...

Which approach better predicts diabetes: Traditional econometric methods or machine learning? Evidence from a cross-sectional study in South Korea.

To prevent chronic disease from getting worse, it is important to detect and predict it at an early ...

Machine learning-based prediction of vesicoureteral reflux outcomes in infants under antibiotic prophylaxis.

We aimed to investigate the independent outcome predictors of continuous antibiotic prophylaxis (CAP...

Artificial intelligence in chronic kidney disease management: a scoping review.

Chronic kidney disease (CKD) is a major public health problem worldwide associated with cardiovascu...

Predicting intra-abdominal hypertension using anthropometric measurements and machine learning.

Almost one in four critically ill patients suffer from intra-abdominal hypertension (IAH). Currently...

Monitoring kidney microanatomy during ischemia-reperfusion using ANFIS optimized CNN.

Kidney disease is a dangerous disease that affects human health and causes various defects. Renal mi...

Construction of a machine learning-based interpretable prediction model for acute kidney injury in hospitalized patients.

In this observational study, we used data from 59,936 hospitalized adults to construct a model. For ...

Machine Learning to Assist in Managing Acute Kidney Injury in General Wards: Multicenter Retrospective Study.

BACKGROUND: Most artificial intelligence-based research on acute kidney injury (AKI) prediction has ...

Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management.

Hypertension presents the largest modifiable public health challenge due to its high prevalence, its...

Tlalpan 2020 Case Study: Enhancing Uric Acid Level Prediction with Machine Learning Regression and Cross-Feature Selection.

Uric acid is a key metabolic byproduct of purine degradation and plays a dual role in human health....

Histopathology based AI model predicts anti-angiogenic therapy response in renal cancer clinical trial.

Anti-angiogenic (AA) therapy is a cornerstone of metastatic clear cell renal cell carcinoma (ccRCC) ...

Artificial intelligence for predicting interstitial fibrosis and tubular atrophy using diagnostic ultrasound imaging and biomarkers.

BACKGROUND: Chronic kidney disease (CKD) is a global health concern characterised by irreversible re...

Current Applications and Developments of Natural Language Processing in Kidney Transplantation: A Scoping Review.

BACKGROUND AND OBJECTIVE: Natural language processing (NLP) is a subfield of artificial intelligence...

Machine learning-based prediction models for renal impairment in Chinese adults with hyperuricaemia: risk factor analysis.

In hyperuricaemic populations, multiple factors may contribute to impaired renal function. This stud...

A network toxicology and machine learning approach to investigate the mechanism of kidney injury from melamine and cyanuric acid co-exposure.

BACKGROUND: Within the past two decades, high-profile cases of melamine (MA) exposure have raised si...

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