U.S., Feb. 8 -- ClinicalTrials.gov registry received information related to the study (NCT06814847) titled 'ARTIFICIAL INTELLIGENCE-BASED ANALYSIS of UROFLOWMETRY PATTERNS in CHILDREN: a MACHINE LEARNING PERSPECTIVE' on Feb. 03.
Brief Summary: Uroflowmetry is the one of the most commonly used non-invasive test for evaluating children with lower urinary tract symptoms (LUTS). However, studies have highlighted a weak agreement among experts in interpreting uroflowmetry patterns. This study aims to assess the impact of machine learning models, which have become increasingly prevalent in medicine, on the interpretation of uroflowmetry patterns.
Study Start Date: Oct. 01, 2024
Study Type: OBSERVATIONAL
Condition:
Voiding Dysfunction
Voiding...