Nephrology

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

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Diabetes: Non-Invasive Blood Glucose Monitoring Using Federated Learning with Biosensor Signals.

Diabetes is a growing global health concern, affecting millions and leading to severe complications ...

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 diseas...

Gut microbiome research: Revealing the pathological mechanisms and treatment strategies of type 2 diabetes.

The high prevalence and disability rate of type 2 diabetes (T2D) caused a huge social burden to the ...

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 m...

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,...

Tumor-educated platelets in lung cancer.

Non-invasive diagnostic monitoring techniques have become essential for treating lung cancer (LC), w...

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 focus...

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-...

MXene-enabled organic synaptic fiber for ultralow-power and biochemical-mediated neuromorphic transistor.

Fibrous bioelectronic provides an intrinsically accessible platform for artificial nerve and real-ti...

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 c...

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 ...

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...

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 ...

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 ra...

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