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Review
. 2025 Mar;44(3):616-621.
doi: 10.1002/nau.25606. Epub 2024 Oct 25.

How Can We Show That Artificial Intelligence May Improve Our Assessment and Management of Lower Urinary Tract Dysfunctions?-ICI-RS 2024

Enrico Finazzi Agrò  1   2 , Eleonora Rosato  2 , George Bou Kheir  3 , Kevin Rademakers  4 , Márcio Augusto Averbeck  5   6 , Tufan Tarcan  7   8 , Hashim Hashim  9 , Andrew Gammie  9 , Sanjay Sinha  10 , Qi-Xiang Song  11 , Rayan Mohamed-Ahmed  12 , Anasofia Da Silva  13 , Riccardo Lombardo  14 , Paul Abrams  9 , Alan Wein  15 , Glenn T Werneburg  16
Affiliations
Review

How Can We Show That Artificial Intelligence May Improve Our Assessment and Management of Lower Urinary Tract Dysfunctions?-ICI-RS 2024

Enrico Finazzi Agrò et al. Neurourol Urodyn. 2025 Mar.

Abstract

Aims: The integration of artificial intelligence (AI) into functional urology management must be assessed for its clinical utility, but hopefully will change, perhaps to revolutionize the way LUTD and other conditions are assessed, the aim being to offer patients more rapid and effective management which enhances patient outcomes. The aim of this proposal, discussed at the ICI-RS annual meeting, is to evaluate the available evidence on AI and the way it might change the approach to urodynamic (UDS) diagnoses, including overactive bladder syndrome (OAB), and perhaps other LUTDs such as bladder outflow obstruction.

Methods: A compendium of discussion based on the current evidence related to AI and its potential applications in UDS and OAB.

Results: AI-powered diagnostic tools are being developed to analyze complex datasets from urodynamic studies, imaging, and other diagnostic tests. AI systems can leverage large volumes of clinical data to recommend personalized treatment plans based on individual patient profiles to optimize surgical procedures, enhance diagnostic precision, tailor the therapy, reduce the risk of complications, and improve outcomes. In the future, AI will be able to provide tailored counseling regarding the outcomes and potential side effects of drugs and procedures to a given patient.

Conclusion: AI's role in functional urology has been poorly investigated, and its implementation across several areas may improve clinical care and the pathophysiological understanding of functional urologic conditions.

Keywords: artificial intelligence; big data; functional urology; lower urinary tract dysfunction; machine learning; overactive bladder; urodynamics.

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References

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