Artificial intelligence-assisted uroflowmetry and automated evaluation of lower urinary system symptoms
The study successfully established an AI-assisted diagnostic framework that markedly improves the automated evaluation of uroflowmetry data and lower urinary tract symptoms. This innovative approach offers a robust alternative to traditional diagnostic practices by reducing subjectivity and enhancing diagnostic accuracy, thereby paving the way for more personalized and effective management of urinary disorders.
Authors
- Hakan Şığva (ORCID: https://orcid.org/0000-0003-1587-6796)
- Kadir Körpe (ORCID: https://orcid.org/0000-0001-7159-1272)
- A Alvarado Duran (ORCID: https://orcid.org/0000-0002-9990-1516)
- Berat Deniz
- Mehmet Sevim
Institutions
- Education Training And Research (US)
Publication Details
- Journal
- Urologia Journal
- Published
- 2025-12-27
- DOI
- https://doi.org/10.1177/03915603251406813
- Primary Topic
- Urinary Bladder and Prostate Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00