Latest AI and machine learning research in nephrology for healthcare professionals.
BACKGROUND: Glomerular hematuria (GH) is a key parameter assessed during urine analysis that is poor...
BACKGROUND: Due to altered drug clearance, renal impairment necessitates drug dose adjustments to pr...
INTRODUCTION: Diabetic kidney disease (DKD) and diabetic nephropathy (DN) affect around 40% of diabe...
BACKGROUND AND OBJECTIVE: The fluorescence resonance energy transfer (FRET) two-hybrid assay enables...
BACKGROUND: Hypertension is a major contributor to cardiovascular morbidity and mortality. Its heter...
BACKGROUND: Cardiovascular disease (CVD) and cancer are leading causes of mortality, often coexistin...
BACKGROUND: Several omics methods have been successfully used in hypertension prediction. However, t...
AIMS: While cardiovascular-kidney-metabolic (CKM) syndrome has been recognised as a continuum of int...
OBJECTIVE: This study presents an independent clinical evaluation of Dr.Noon CVD, a commercially dev...
ETHNOPHARMACOLOGICAL RELEVANCE: Gelsemium elegans Benth. (G. elegans) is a highly toxic medicinal pl...
INTRODUCTION: Identifying patient characteristics predictive of treatment response is crucial for op...
OBJECTIVE: To examine cross-sectional and longitudinal associations between vascular risk factors, A...
BACKGROUND: This study aims to develop a Machine Learning (ML) model to predict the initial diagnosi...
BACKGROUND: Predicting prolonged intensive care unit (ICU) length of stay (LOS) remains challenging,...
Acute kidney injury (AKI) is a devastating complication of acute illness that affects adults and chi...
BACKGROUND: Predicting clinical and radiological outcomes of epidermal growth factor receptor tyrosi...
BACKGROUND: Worsening renal function (WRF) during acute decompensated heart failure (ADHF) therapy p...
BACKGROUND: Depression is a prevalent and debilitating mental disorder with limited treatment option...
ETHNOPHARMACOLOGICAL RELEVANCE: Nelumbinis Receptaculum (NR) were hemostatic herbal medicines for tr...
OBJECTIVE: This study aims to develop a low-dose CT-based, fully automated deep learning tool for sc...
OBJECTIVE: To develop and internally validate a machine-learning model for the early prediction of p...