End Stage Renal Disease

FDG-PET Medullary Total Tumor Volume Highlights High-Risk Newly Diagnosed Multiple Myeloma Patients in CASSIOPEIA Trial.

This study aimed to assess the prognostic value of medullary total metabolic tumor volume (mTMTV) de...

From algorithms to action: Risk stratification for arteriovenous fistula failure in hemodialysis.

BACKGROUND: Arteriovenous fistula (AVF) is the preferred vascular access for hemodialysis, yet prima...

Development and validation of an artificial intelligence-based model for predicting teicoplanin plasma concentrations in intensive care unit patients with pulmonary infections: a retrospective study.

INTRODUCTION: Teicoplanin is widely used to treat pulmonary infections, particularly in critically i...

Machine Learning Prediction of Progression to Dialysis in Patients With Polycystic Kidney Disease: Population-Based Retrospective Cohort Study.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD), characterized by progressive cyst ...

Advanced artificial intelligence vs simpler models for 1-year death prediction among patients receiving hemodialysis.

OBJECTIVES: We evaluated the data requirement for modern AI tools to outperform simpler models in pr...

A complete blood count-based machine learning model for rapid differentiation of aplastic anemia, immune thrombocytopenia, and myelodysplastic syndromes in routine clinical practice.

BACKGROUND: Accurate differentiation of common hematologic disorders remains challenging in routine ...

An interpretable nomogram for predicting sleep disturbance risk in maintenance hemodialysis patients.

BACKGROUND: This study aimed to develop and validate an interpretable nomogram to predict the risk o...

Preoperative Risk Score for Mortality Within 3 Years of Elective Aortobifemoral Artery Bypass.

BACKGROUND: The purpose of this study was to create a risk score for mortality within 3 years of ele...

Cross-validation strategies under data dependency: An example with anemia prediction in sheep using ocular conjunctiva images.

Computer vision techniques have been increasingly used in livestock farming for tasks such as animal...

Predictive divergence in machine learning models for clinical mortality risk: A multicohort study of covid-19 patients.

BACKGROUND: Machine learning (ML) algorithms are increasingly used in healthcare to support clinical...

Comparison of the diagnostic performance of machine learning algorithms for differentiating iron deficiency anemia and thalassemia.

Exploring factors and models to predict post-dialysis volume overload status in maintenance hemodialysis patients based on pre-dialysis parameters.

OBJECTIVE: This study explored factors and models to predict post-dialysis volume overload status in...

Predicting mortality and short-term outcomes of continuous kidney replacement therapies in neonates and infants.

BACKGROUND: Continuous kidney replacement therapy (CKRT) has emerged as a valuable treatment option ...

Deep learning for fast screening and localization of spinal dural arteriovenous fistulas to enhance clinical workflow.

Manual processing of spinal CTA images for detecting dural arteriovenous fistulas (SDAVF) is laborio...

msCNN-PLM-FAD: Enhanced predicting FAD binding sites by using protein language representation combined with multiple separable windows convolutional neural networks.

The FAD binding sites classification problem is crucial because it is directly related to many disea...

Association between hypothermic machine perfusion parameters and graft function in deceased donor kidney transplantation.

BACKGROUND: Kidney transplantation (KT) is the most effective treatment for end-stage renal disease....

Artificial intelligence in pediatric nephrology: current applications and emerging frameworks for evidence generation.

Artificial intelligence (AI) is rapidly transforming many areas of medicine. Pediatric nephrology ma...

Regional brain age is decreased in children with sickle cell anemia.

DeepBrainNet, a machine learning tool, uses magnetic resonance imaging (MRI) to predict an individua...

Regional brain age is decreased in children with sickle cell anemia.

DeepBrainNet, a machine learning tool, uses magnetic resonance imaging (MRI) to predict an individua...

Artificial Intelligence-Based Analysis of Central Nervous System Vasculopathy in Pediatric Sickle Cell Anemia.

In children with sickle cell anemia (SCA), central nervous system (CNS) complications such as chroni...

Prediction of Postoperative Pancreatic Fistula Occurrence by the Pancreatic Stump Shape and Remnant Pancreatic Volume Measured Using AI-Guided Three-Dimensional Simulation.

BACKGROUND: When three-dimensional computer graphics (3DCG) images are used, artificial intelligence...