Huang et al, present a literature review on the applications of AI in urodynamics, specifically in the interpretation of UDS test results and enhancing the precision of diagnosis. The papers were selected based on PRISMA guidelines, using an 8x10 keyword matrix from Google Scholar and PubMed between 2020 and 2024. Full text reviews were then conducted following predefined guides and comparative data tables were constructed utilizing information such as primary goal, study design, sample size, etc. The 248 resulting papers were filtered down further until 31 relevant articles remained. These were then separated into three sections depending on the functionality of the AI: reducing invasiveness, enhancing diagnosis, predicting prognosis. The review shows that there has been an increase in the application of AI in urodynamics and there are possibilities to improve the management of large data pools. The AIs have the ability to find novel patterns that can enhance diagnostic precision, prognostic predictions, and treatment guidance. However, there are limitations in the form of the lack of external validation, the substantial required data sets and the limited sample sizes of existing studies.