Latest AI and machine learning research in urology for healthcare professionals.
Urinary incontinence is one of the main concerns for patients after radical prostatectomy. Differences in surgical experience among surgeons could partly explain the wide range of frequencies observed. Our aim was to evaluate the association between the surgeons` experience and center caseload with relation to urinary continence recovery after Retzius-sparing robot-assisted radical prostatectomy (...
BACKGROUND: We investigated the feasibility of a deep learning algorithm (DLA) based on apparent diffusion coefficient (ADC) maps for the segmentation and discrimination of clinically significant cancer (CSC, Gleason score ≥ 7) from non-CSC in patients with prostate cancer (PCa).
Artificial intelligence (AI) is revolutionizing prostate cancer genomics research. By leveraging machine learning and deep learning algorithms, resear...
Endourology is ripe with information that includes patient factors, laboratory tests, outcomes, and visual data, which is becoming increasingly comple...
The use of artificial intelligence (AI) in medicine and in urology specifically has increased over the past few years, during which time it has enable...
T3a renal masses include a diverse group of tumors that invade the perirenal and/or sinus fat, pelvicaliceal system, or renal vein. The majority of c...
PURPOSE: To report long-term oncologic and functional outcomes of a large consecutive single center series of Robot-assisted radical cystectomy (RARC)...
: Multiple factors are associated with postoperative functional outcomes, such as acute kidney injury (AKI), following partial nephrectomy (PN). The p...
PURPOSE: To provide an update on the diverse, contemporary urological applications of the Hugo™ RAS system.
BACKGROUND AND PURPOSE: The Stage, Size, Grade and Necrosis (SSIGN) score is the most commonly used prognostic model in clear cell renal cell carcinom...
INTRODUCTION: Complex oncological procedures pose various surgical challenges including dissection in distinct tissue planes and preservation of vulne...
BACKGROUND: Weakly supervised learning promises reduced annotation effort while maintaining performance.
OBJECTIVES: To evaluate a fully automatic deep learning system to detect and segment clinically significant prostate cancer (csPCa) on same-vendor pro...
PURPOSE: To evaluate the impact of a commercially available deep learning-based reconstruction (DLR) algorithm with varying combinations of DLR noise ...
Androgen receptor (AR), a steroid receptor, plays a pivotal role in the pathogenesis of prostate cancer (PCa). AR controls the transcription of genes ...
OBJECTIVES: This study aimed to investigate the characteristics of patients who report improvement in quality of life (QOL) related to urinary status ...
Artificial intelligence (AI) has the potential to transform pathologic diagnosis and cancer patient management as a predictive and prognostic biomarke...
INTRODUCTION: This study was performed to evaluate the safety and efficacy of lymph node dissection (LND) during robot-assisted radical cystectomy (RA...
Whether you are a surgical, medical, or radiation oncologist, the care goals remain the same, that is, achieving a durable treatment response. For pat...