Latest AI and machine learning research in nephrology for healthcare professionals.
Deep learning-based organs/structures-at-risk(OARs) auto-contouring models can improve radiotherapy ...
In routine care, individuals identified a priori as high-risk are usually tested for conditions more...
Background: People with Multiple Long-Term Conditions (MLTC) experience higher rates of organ failur...
Medical image super-resolution (MedSR) is essential for improving diagnostic precision across divers...
Objectives This study aimed to develop and validate machine learning models to predict in-hospital m...
Background: Timely, uncertainty-aware forecasting from irregular electronic health records (EHR) can...
Robotic ultrasound has advanced local image-driven control, contact regulation, and view optimizatio...
Background Polycyclic aromatic hydrocarbons (PAHs) and volatile organic compounds (VOCs) are combust...
Motivation: Multi-omics integration can improve cancer subtyping, but modality informativeness and n...
Progression to dialysis or end-stage renal disease is a rare but clinically important outcome. Clini...
Background: Inappropriate normalization can lead to data leakage and overfitting in machine learning...
Background: Chronic conditions such as hypertension can significantly disrupt daily life and emotion...
Background: Medical imaging, especially computed tomography and magnetic resonance imaging, is essen...
Extracellular vesicles are increasingly recognized as important carriers of disease-associated molec...
Accurate early prediction of Acute Kidney Injury (AKI) is critical for timely clinical intervention....
Rational design of covalent inhibitors requires simultaneously optimizing multiple properties, such ...
Lung transplantation programs must decide when bilateral lung transplantation (BLT) offers meaningfu...
Hybrid Quantum Neural Networks (HQNNs) have recently emerged as a promising paradigm for near-term q...
Antimicrobial peptides (AMPs) are key effectors of host defence, however, their functional deploymen...
Adaptive medical AI models often face performance drops in dynamic clinical environments due to data...
Stain variability is a pervasive source of distribution shift and potential shortcut learning in ren...