Nephrology

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

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Integrating radiomics and gene expression by mapping on the image with improved DeepInsight for clear cell renal cell carcinoma.

BACKGROUND: Radiomics analysis extracts high-dimensional features from medical images, which are use...

Supercapacitor Materials Database Generated using Web Scrapping and Natural Language Processing.

Electrochemical energy storage plays a vital role in achieving environmental sustainability. Superca...

Liver fibrosis progression analyzed with AI predicts renal decline.

BACKGROUND & AIMS: The relationship between biopsy-proven liver fibrosis progression and renal funct...

Machine learning prediction of glaucoma by heavy metal exposure: results from the National Health and Nutrition Examination Survey 2005 to 2008.

Using follow-up data from the National Health and Nutrition Examination Survey (NHANES) database, we...

Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients.

Post-Liver transplantation (LT) survival rates stagnate, with biliary complications (BC) as a major ...

Integration of radiomic and deep features to reliably differentiate benign renal lesions from renal cell carcinoma.

PURPOSE: Accurate differentiation of benign renal lesions from renal cell carcinoma (RCC) is crucial...

Multifunctional Fiber Robotics with Low Mechanical Hysteresis for Magnetic Navigation and Inhaled Gas Sensing.

Recently, increasing research attention has been directed toward detecting the distribution of hazar...

Diagnosis of Chronic Kidney Disease Using Retinal Imaging and Urine Dipstick Data: Multimodal Deep Learning Approach.

BACKGROUND: Chronic kidney disease (CKD) is a prevalent condition with significant global health imp...

Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses.

Treatment decisions for an incidental renal mass are mostly made with pathologic uncertainty. Improv...

Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets.

Diabetes Mellitus (DM) is a global health challenge, and accurate early detection is critical for ef...

Artificial intelligence in kidney transplantation: a 30-year bibliometric analysis of research trends, innovations, and future directions.

Kidney transplantation is the definitive treatment for end-stage renal disease (ESRD), yet challenge...

Machine learning for classifying chronic kidney disease and predicting creatinine levels using at-home measurements.

Chronic kidney disease (CKD) is a global health concern with early detection playing a pivotal role ...

Constructing a machine learning model for systemic infection after kidney stone surgery based on CT values.

This study aims to develop a machine learning model utilizing Computed Tomography (CT) values to pre...

A Fully Automated Artificial Intelligence-Based Approach to Predict Renal Function After Radical or Partial Nephrectomy.

OBJECTIVE: To test if our artificial intelligence (AI)-postoperative glomerular filtration rate (GFR...

Multimodal convolutional neural networks for the prediction of acute kidney injury in the intensive care.

Increased monitoring of health-related data for ICU patients holds great potential for the early pre...

Development and Evaluation of a Deep Learning-Based Pulmonary Hypertension Screening Algorithm Using a Digital Stethoscope.

BACKGROUND: Despite the poor outcomes related to the presence of pulmonary hypertension, it often go...

Developing clinical prognostic models to predict graft survival after renal transplantation: comparison of statistical and machine learning models.

INTRODUCTION: Renal transplantation is a critical treatment for end-stage renal disease, but graft f...

The Liver Intensive Care Unit.

Major advances in managing critically ill patients with liver disease have improved their prognosis ...

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