ArticleNeurourology and urodynamics2026
What Is Required for AI to Improve the Assessment and Treatment of Patients With Lower Urinary Tract Dysfunction? ICI-RS 2025.
Article in Neurourology and urodynamics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Global Research Trends in Pediatric Lower Urinary Tract Dysfunction: A Bibliometric Analysis (1945-2026).Healthcare (Basel, Switzerland) · 2026Article
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Authors and funding
16 authors.
Funding
Abstract
introductionArtificial intelligence (AI) is poised to improve the diagnosis and management of lower urinary tract dysfunction (LUTD). Its effective deployment requires prioritization, regulatory oversight, rigorous validation, and clinician and patient engagement.
methodsThe Think Tank at the International Consultation on Incontinence-Research Society (ICI-RS) 2025 evaluated key considerations for successful AI implementation into LUTD clinical care. The topics included clinical triage framework, regulatory and legal principles, levels of evidence required for validation, and clinician and patient engagement to guide development. The group developed a narrative of the pressing matters related to AI implementation and a list of proposed research questions, which, when addressed, will help shape the future of the field.
resultsLUTD topics that should be prioritized for AI implementation include high-burden conditions with high unmet need such as neurogenic LUTD, bladder outlet obstruction, and overactive bladder. Regulatory frameworks such as the EU AI Act and the U.S. "Software as a Medical Device" and its associated guidance promote safety, transparency, and accountability. AI solutions should be as rigorously evaluated as other clinical devices or drug agents. Patient and clinician engagement are paramount to ensure innovation aligns with the pressing needs of patients and clinicians.
conclusionsAI's integration into LUTD care requires cross-disciplinary collaboration, prospective validation, and legal and ethical frameworks. AI must be developed and implemented with a strong focus on transparency, trust, and patient-centered care. CLINICAL
trial registrationThis study is not a clinical trial and thus does not warrant registration as such.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.