PURPOSE: We developed Machine learning (ML) algorithms to predict ureteroscopy (URS) outcomes, offering insights into diagnosis and treatment planning, personalised care and improved clinical decision-making.
Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences
Jan 25, 2024
OBJECTIVES: To analyze the association of serum heparin-binding protein (HBP) and C-reactive protein (CRP) levels with urosepsis following flexible ureteroscopic lithotripsy (FURL) and to construct a back propagation neural network prediction model.
The aim of this study is to present the first Italian experience with robotic-assisted retrograde intrarenal surgery (rRIRS) using the Ily platform. Procedures were performed for renal stones using the Ily Robot (STERLAB, Vallauris, France), which is...
PURPOSE OF REVIEW: The pace of technology development with single-use endoscopy has led to a range of disposable ureteroscopes. We review the development of single-use scopes, deconstruct the basic design and functional characteristics of available d...
PURPOSE OF REVIEW: There has a been rapid progress in the use of artificial intelligence in all aspects of healthcare, and in urology, this is particularly astute in the overall management of urolithiasis. This article reviews advances in the use of ...
Journal of the College of Physicians and Surgeons--Pakistan : JCPSP
Dec 1, 2019
Nephrogenic adenoma is a rare and benign tumour of the urinary tract thought to be caused by metaplastic change of native urothelial tissue. The majority of cases arise in the bladder, with very few cases affecting the ureter reported in the literatu...
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