Nephrology

Commentary on "develop a radiomics-based machine learning model to predict the stone-free rate post-percutaneous nephrolithotomy".

Data-driven prediction of continuous renal replacement therapy survival.

Continuous renal replacement therapy (CRRT) is a form of dialysis prescribed to severely ill patients who cannot tolerate regular hemodialysis. However, as the patients are typically very ill to begin with, there is always uncertainty whether they will survive during or after CRRT treatment. Because of outcome uncertainty, a large percentage of patients treated with CRRT do not survive, utilizing ...

Identification of immune-related genes and small-molecule drugs in hypertension-induced left ventricular hypertrophy based on machine learning algorithms and molecular docking.

BACKGROUND: Left ventricular hypertrophy (LVH) is a common consequence of hypertension and can lead to heart failure. The immune response plays an imp...

Toward human-like adaptability in robotics through a retention-engineered synaptic control system.

Although advanced robots can adeptly mimic human movement and aesthetics, they are still unable to adapt or evolve in response to external experiences...

Predicting renal damage in children with IgA vasculitis by machine learning.

BACKGROUND: Children with IgA Vasculitis (IgAV) may develop renal complications, which can impact their long-term prognosis. This study aimed to build...

A simple machine learning model for the prediction of acute kidney injury following noncardiac surgery in geriatric patients: a prospective cohort study.

BACKGROUND: Surgery in geriatric patients often poses risk of major postoperative complications. Acute kidney injury (AKI) is a common complication fo...

Diagnosis and classification of kidney transplant rejection using machine learning-assisted surface-enhanced Raman spectroscopy using a single drop of serum.

The quest to reduce kidney transplant rejection has emphasized the urgent requirement for the development of non-invasive, precise diagnostic technolo...

Molybdenum Disulfide-Assisted Spontaneous Formation of Multistacked Gold Nanoparticles for Deep Learning-Integrated Surface-Enhanced Raman Scattering.

Several fabrication methods have been developed for label-free detection in various fields. However, fabricating high-density and highly ordered nanos...

RISK FACTORS FOR ACUTE KIDNEY INJURY ASSOCIATED WITH SEVERE HYPOTHYROIDISM.

OBJECTIVE: This study aims to investigate the factors affecting development of acute kidney injury (AKI) in patients with severe hypothyroidism.

Integrative approach for efficient detection of kidney stones based on improved deep neural network architecture.

In today's digital world, with growing population and increasing pollution, unhealthy lifestyle habits like irregular eating, junk food consumption, a...

Machine learning constructs a diagnostic prediction model for calculous pyonephrosis.

In order to provide decision-making support for the auxiliary diagnosis and individualized treatment of calculous pyonephrosis, the study aims to anal...

The emerging role of generative artificial intelligence in transplant medicine.

Generative artificial intelligence (AI), a subset of machine learning that creates new content based on training data, has witnessed tremendous advanc...

Smart solutions in hypertension diagnosis and management: a deep dive into artificial intelligence and modern wearables for blood pressure monitoring.

Hypertension, a widespread cardiovascular issue, presents a major global health challenge. Traditional diagnosis and treatment methods involve periodi...

Study of machine learning techniques for outcome assessment of leptospirosis patients.

Leptospirosis is a global disease that impacts people worldwide, particularly in humid and tropical regions, and is associated with significant socio-...

Multimodal data integration using machine learning to predict the risk of clear cell renal cancer metastasis: a retrospective multicentre study.

PURPOSE: To develop and validate a predictive combined model for metastasis in patients with clear cell renal cell carcinoma (ccRCC) by integrating mu...

CT-based radiomics of machine-learning to screen high-risk individuals with kidney stones.

Screening high-risk populations is crucial for the prevention and treatment of kidney stones. Here, we employed radiomics to screen high-risk patients...

Deep learning-based pathological prediction of lymph node metastasis for patient with renal cell carcinoma from primary whole slide images.

BACKGROUND: Metastasis renal cell carcinoma (RCC) patients have extremely high mortality rate. A predictive model for RCC micrometastasis based on pat...

Association between machine learning-assisted heavy metal exposures and diabetic kidney disease: a cross-sectional survey and Mendelian randomization analysis.

BACKGROUND AND OBJECTIVE: Heavy metals, ubiquitous in the environment, pose a global public health concern. The correlation between these and diabetic...

Dynamic Individualized Risk Prediction in IgA Nephropathy: Entering the Era of Artificial Intelligence.

Machine Learning-Aided Decision-Making Model for the Discontinuation of Continuous Renal Replacement Therapy.

INTRODUCTION: Continuous renal replacement therapy (CRRT) is a primary form of renal support for patients with acute kidney injury in an intensive car...