Clinical Trial: Artificial Intelligence-Based Analysis of Uroflowmetry Patterns in Children: a Machine Learning Perspective
Study Status: COMPLETED
Recruit Status: COMPLETED
Condition: Voiding Dysfunction
Study Type: OBSERVATIONAL
Official Title: Interpretation of Uroflowmetry Samples from Pediatric Patients by Clinicians and Introduction to Artificial Intelligence, and Interpretation of the Samples by Artificial Intelligence
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.
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