Chronic kidney disease (CKD) affects over 850 million people globally, and the need to prevent its development and progression is urgent. During the past decade, new perspectives have arisen related to the quality and precision of care for CKD, owing...
We aimed to evaluate the renoprotective effects of remote ischemic preconditioning (RIPC) in patients undergoing robot-assisted laparoscopic partial nephrectomy (RAPN). Data from 59 patients with solitary renal tumors who underwent RAPN with RIPC com...
AIM: To investigate the feasibility of using deep learning (DL) to differentiate normal from abnormal (or scarred) kidneys using technetium-99m dimercaptosuccinic acid (Tc-DMSA) single-photon-emission computed tomography (SPECT) in paediatric patient...
The renal vasculature, acting as a resource distribution network, plays an important role in both the physiology and pathophysiology of the kidney. However, no imaging techniques allow an assessment of the structure and function of the renal vasculat...
Multi-instance learning (MIL) is widely adop- ted for automatic whole slide image (WSI) analysis and it usually consists of two stages, i.e., instance feature extraction and feature aggregation. However, due to the "weak supervision" of slide-level l...
BACKGROUND: An empirical selective clamping strategy based on the direction of the arterial branches can lead to failures during partial nephrectomy, even when assisted by three-dimensional virtual models (3DVMs).
Recovery from acute kidney injury can vary widely in patients and in animal models. Immunofluorescence staining can provide spatial information about heterogeneous injury responses, but often only a fraction of stained tissue is analyzed. Deep learni...