Within the literature concerning modern machine learning techniques applied to the medical field, there is a growing interest in the application of these technologies to the nephrological area, especially regarding the study of renal pathologies, bec...
IEEE journal of biomedical and health informatics
Jul 1, 2022
Semi-supervised learning has substantially advanced medical image segmentation since it alleviates the heavy burden of acquiring the costly expert-examined annotations. Especially, the consistency-based approaches have attracted more attention for th...
Journal of the American Society of Nephrology : JASN
Jun 29, 2022
BACKGROUND: Total kidney volume (TKV) is an important imaging biomarker in autosomal dominant polycystic kidney disease (ADPKD). Manual computation of TKV, particularly with the exclusion of exophytic cysts, is laborious and time consuming.
We sought to describe the development of the robotic urology program at Sindh Institute of Urology and Transplantation (SIUT) and the feasibility of transitioning from the da Vinci to Versius robotic systems. The SIUT robotics program began in 2017 u...
BACKGROUND: Despite an expected increase in prostate cancer (PCa) incidence in the renal transplant recipient (RTR) population in the near future, robot-assisted radical prostatectomy (RARP) in these patients has been poorly detailed. It is not well ...
Current opinion in nephrology and hypertension
Jun 10, 2022
PURPOSE OF REVIEW: We seek to determine recent advances in kidney pathophysiology that have been enabled or enhanced by artificial intelligence. We describe some of the challenges in the field as well as future directions.
Fraley's Syndrome is a rare anatomic vascular malformation described in 1966 where an aberrant crossing vessel compresses the upper infundibulum and leads to upper calyx massive dilation. It is mostly asymptomatic and the diagnosis often missed; howe...
PURPOSE: We investigated the feasibility of measuring the hydronephrosis area to renal parenchyma (HARP) ratio from ultrasound images using a deep-learning network.
The aim of the study described here was to investigate the value of different machine learning models based on the clinical and radiomic features of 2-D ultrasound images to evaluate post-transplant renal function (pTRF). We included 233 patients who...
The study's aim was to externally validate a new predictive model for the new baseline glomerular filtration rate (NB-GFR) postnephrectomy among Japanese patients. Patients with renal tumors who underwent radical nephrectomy (RN) or robot-assisted ...
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