Latest AI and machine learning research in nephrology for healthcare professionals.
Near-perfect classification of small clinical datasets can hinge on preprocessing, data leakage, mis...
Cardiotocography (CTG) is the standard of care for intrapartum fetal monitoring, yet its poor specif...
Purpose: Quantitative susceptibility mapping (QSM) provides venous contrast through the paramagnetic...
Timely detection of fetal distress during labor is a central pursuit of modern obstetric care. The p...
Postoperative acute kidney injury (AKI) after major non-cardiac surgery carries substantial morbidit...
Radiomics provides quantitative descriptions of tumour appearance that may complement disease-specif...
Deep learning segmentation of renal tumors requires large annotated datasets, yet clinical deploymen...
Counterfactual simulation with a clinical world model means fixing a patient's history, changing the...
The kidney is a critical soft-tissue organ responsible for blood filtration. Accurate constitutive m...
Background: Hypertension is the most important modifiable cardiovascular risk factor worldwide, and ...
Recent innovations in deep learning have significantly enhanced the diagnosis of medical images, alt...
Fine-grained evaluation of glomerular pathology must distinguish normal glomeruli from abnormalities...
A large share of late-stage clinical trial failures reflects not the underlying biology of the targe...
Background Acute kidney injury (AKI)-to-chronic kidney disease (CKD) transition is associated with d...
Drug repurposing offers a cost-effective path to new therapies for triple-negative breast cancer (TN...
Multi-phase contrast-enhanced computed tomography (CT) is the gold standard for renal cell carcinoma...
Background Pre-implantation biopsy utility for deceased-donor kidney acceptance is controversial due...
Cranial nerves (CNs) play essential roles in sensory, motor, and autonomic functions. Accurate CN pa...
Deep learning models for CT scan analysis are often limited by the scarcity of precise pixel-level a...
Segmentation of complex structures in X-ray tomographic data is a fundamental task in biomedical res...
We convert black-box clinical prediction models for tabular data into standalone nomograms that can ...