Unsupervised machine learning approach to interpret complex lower urinary tract symptoms and their impact on quality of life in adult women.
Journal:
World journal of urology
Published Date:
Aug 4, 2025
Abstract
PURPOSE: To identify clinically meaningful clusters of lower urinary tract symptoms (LUTS) in adult women using an unsupervised machine learning approach and to examine their associations with patient-centered outcomes, including quality of life (QoL), willingness to pay (WTP) for treatment, and physician visits.