Nephrology

Development and validation of multi-center serum creatinine-based models for noninvasive prediction of kidney fibrosis in chronic kidney disease.

OBJECTIVE: Kidney fibrosis is a key pathological feature in the progression of chronic kidney disease (CKD), traditionally diagnosed through invasive kidney biopsy. This study aimed to develop and validate a noninvasive, multi-center predictive model incorporating machine learning (ML) for assessing kidney fibrosis severity using biochemical markers.

Identifying potential risk genes for clear cell renal cell carcinoma with deep reinforcement learning.

Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal cell carcinoma. However, our understanding of ccRCC risk genes remains limited. This gap in knowledge poses challenges to the effective diagnosis and treatment of ccRCC. To address this problem, we propose a deep reinforcement learning-based computational approach named RL-GenRisk to identify ccRCC risk genes. Distinct fro...

Rapid diagnosis of membranous nephropathy based on kidney tissue Raman spectroscopy and deep learning.

Membranous nephropathy (MN) is one of the most common glomerular diseases. Although the diagnostic method based on serum PLA2R antibodies has graduall...

Tumor-educated platelets in lung cancer.

Non-invasive diagnostic monitoring techniques have become essential for treating lung cancer (LC), which continues to be the primary cause of cancer-r...

Using machine learning to investigate the influence of the prenatal chemical exposome on neurodevelopment of young children.

Research investigating the prenatal chemical exposome and child neurodevelopment has typically focused on a limited number of chemical exposures and c...

Effects of super high-flux vitamin E-coated and medium cut-off dialyzers on uremic toxins removal and biocompatibility: the E-FLUX randomized controlled study.

BACKGROUND: Medium cut-off hemodialysis (MCO-HD) improves removal of middle molecules (MM) uremic toxins. The effects of the novel super high-flux vit...

Leveraging ensemble convolutional neural networks and metaheuristic strategies for advanced kidney disease screening and classification.

To address the public health issue of renal failure and the global shortage of nephrologists, an AI-based system has been developed to automatically i...

Interpretable Machine Learning Radiomics Model Predicts 5-year Recurrence-Free Survival in Non-metastatic Clear Cell Renal Cell Carcinoma: A Multicenter and Retrospective Cohort Study.

RATIONALE AND OBJECTIVES: To develop and validate a computed tomography (CT) radiomics-based interpretable machine learning (ML) model for predicting ...

Exploring 4 generation EGFR inhibitors: A review of clinical outcomes and structural binding insights.

Epidermal growth factor receptor (EGFR) is a potential target for anticancer therapies and plays a crucial role in cell growth, survival, and metastas...

A Risk Prediction Model (CMC-AKIX) for Postoperative Acute Kidney Injury Using Machine Learning: Algorithm Development and Validation.

BACKGROUND: Postoperative acute kidney injury (AKI) is a significant risk associated with surgeries under general anesthesia, often leading to increas...

Machine learning approach for the prediction of 30-day mortality in patients with sepsis-associated delirium.

This study aimed to develop models for predicting the 30-day mortality of sepsis-associated delirium (SAD) by multiple machine learning (ML) algorithm...

A comparison of neural networks and regression-based approaches for estimating kidney function in pediatric chronic kidney disease: Practical predictive epidemiology for clinical management of a progressive disease.

PURPOSE: Clinical management of pediatric chronic kidney disease requires estimation of glomerular filtration rate (eGFR). Currently, eGFR is determin...

Risk prediction for acute kidney disease and adverse outcomes in patients with chronic obstructive pulmonary disease: an interpretable machine learning approach.

BACKGROUND: Little is known about acute kidney injury (AKI) and acute kidney disease (AKD) in patients with chronic obstructive pulmonary disease (COP...

Machine learning algorithms for diabetic kidney disease risk predictive model of Chinese patients with type 2 diabetes mellitus.

BACKGROUND: Diabetic kidney disease (DKD) is a common and serious complication of diabetic mellitus (DM). More sensitive methods for early DKD predict...

A neural network approach to glomerular filtration rate estimation: a single-centre retrospective audit.

OBJECTIVES: The 2009 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation without race correction factor is frequently used for an est...

Establishing a clinical prediction model for diabetic foot ulcers in type 2 diabetic patients with lower extremity arteriosclerotic occlusion using machine learning.

The burden of diabetic foot ulcers (DFU) is exacerbated in diabetic patients with concomitant arteriosclerotic occlusion disease (ASO) in the lower ex...

Febrile neutropenia management in high-risk neutropenic patients: a narrative review on antibiotic prophylaxis and empirical treatment.

INTRODUCTION: Although febrile neutropenia (FN) remains a major cause of morbidity and mortality in patients with hematologic malignancies and hematop...

Effects of Renal Function on the Multimodal Brain Networks Affecting Mild Cognitive Impairment Converters in End-Stage Renal Disease.

RATIONALE AND OBJECTIVES: Cognitive decline is common in End-Stage Renal Disease (ESRD) patients, yet its neural mechanisms are poorly understood. Thi...

Machine learning models to predict osteoporosis in patients with chronic kidney disease stage 3-5 and end-stage kidney disease.

Chronic kidney disease-mineral bone disorder is a common complication in patients with chronic kidney disease (CKD) and end-stage kidney disease (ESKD...

Urinary biomarkers of kidney transplant rejection.

PURPOSE OF REVIEW: Despite the introduction of many new immunosuppressive medications, allograft rejection remains a significant complication in trans...