Latest AI and machine learning research in nephrology for healthcare professionals.
We present an end-to-end pipeline that converts healthcare policy documents into executable, data-aware Business Process Model and Notation (BPMN) models using large language models (LLMs) for simulation-based policy evaluation. We address the main challenges of automated policy digitization with four contributions: data-grounded BPMN generation with syntax auto-correction, executable augmentation...
Stain variability is a pervasive source of distribution shift and potential shortcut learning in renal pathology AI. We ask whether lupus nephritis glomerular lesion classifiers exploit stain as a shortcut, and how to mitigate such bias without stain or site labels. We curate a multi-center, multi-stain dataset of 9{,}674 glomerular patches (224$\times$224) from 365 WSIs across three centers and f...
Kidney stone disease ranks among the most prevalent conditions in urology, and understanding the composition of these stones is essential for creating...
Clinicians lack precision medicine tools to estimate individualized treatment effects for patients with heart failure (HF). Causal machine learning le...
Introduction: Podocyte injury is central to the pathogenesis of most glomerulonephritides (GN) and causes segmental glomerulosclerotic lesions that pr...
Chronic kidney disease of unknown etiology (CKDu) has emerged as an important public health challenge, particularly in agricultural communities across...
Background: The 2017 American College of Cardiology/American Heart Association (ACC/AHA) guideline lowered diagnostic threshold for hypertension, enco...
Sleep disturbances lead to risk for cardiovascular (CV), metabolic, and neurological diseases. While in-lab polysomnography (PSG) is the gold standard...
Retinal fundus imaging enables low-cost and scalable hypertension (HTN) screening, but HTN-related retinal cues are subtle, yielding high-variance pre...
Accurate segmentation of coronary arteries from computed tomography angiography (CTA) images is of paramount clinical importance for the diagnosis and...
Monocular 3D lane detection remains challenging due to depth ambiguity and weak geometric constraints. Mainstream methods rely on depth guidance, BEV ...
The reliability of artificial intelligence (AI) in medical imaging critically depends on its robustness to heterogeneous and corrupted images acquired...
Deletions in Exon-19 of the epidermal growth factor receptor (EGFR) play a pivotal role in the pathogenesis of non-small cell lung cancer (NSCLC), inf...
Standard deep learning models for image segmentation cannot guarantee topology accuracy, failing to preserve the correct number of connected component...
Spatial graphs provide a lightweight and elegant representation of curvilinear anatomical structures such as blood vessels, lung airways, and neuronal...
Histopathology foundation models (HFMs), pretrained on large-scale cancer datasets, have advanced computational pathology. However, their applicabilit...
Hyperkalemia is a life-threatening electrolyte disorder that is common in patients with chronic kidney disease and heart failure, yet frequent monitor...
Renal cell carcinoma (RCC) with venous tumor thrombus, termed renal intravascular tumor extension (RITE), is associated with aggressive behavior and p...
Rationale Autonomic dysfunction is a hallmark of sepsis pathophysiology, yet its quantification remains challenging. Multiscale entropy (MSE) derived ...
Clear cell renal cell carcinoma (ccRCC) is the leading cause of kidney cancer-related death, but how the tumor microenvironment shapes patient surviva...