Application of artificial intelligence (AI) is one of the hottest topics in medicine. Unlike traditional methods that rely heavily on statistical assumptions, machine learning algorithms can identify highly complex patterns from data, allowing robust...
PURPOSE OF REVIEW: Tumor volume and heterogenicity are associated with diagnosis and prognosis of urological cancers, and assessed by conventional imaging. Quantitative imaging, Radiomics, using advanced mathematical analysis may contain information ...
BACKGROUND: Urologic research often requires data abstraction from unstructured text contained within the electronic health record. A number of natural language processing (NLP) tools have been developed to aid with this time-consuming task; however,...
BACKGROUND: Pelvic lymph node dissection is a procedure performed in gastroenterological surgery, urology, and gynecology. However, due to discrepancies in the understanding of pelvic anatomy among these departments, cross-disciplinary discussions ha...
PURPOSE: This study is a comparative analysis of three Large Language Models (LLMs) evaluating their rate of correct answers (RoCA) and the reliability of generated answers on a set of urological knowledge-based questions spanning different levels of...
BACKGROUND AND OBJECTIVE: Machine learning (ML) is a subset of artificial intelligence that uses data to build algorithms to predict specific outcomes. Few ML studies have examined percutaneous nephrolithotomy (PCNL) outcomes. Our objective was to bu...
Magnetic-assisted robotic surgery (MARS) has been developed to maximize patient benefits of minimally invasive surgery while enhancing surgeon control and visualization. MARS platform (Levita Magnetics) comprises two robotic arms that provide contro...