Machine Vision Augmentation to Detect Detrusor Overactivity in Overactive Bladder: A Frontier of Artificial Intelligence Application in Functional Urology—Proof of Concept Clinical Study
We describe a novel model leveraging AI machine vision to demonstrate statistically increased keypoint deviations on the detrusor vascular network of OAB patients as compared to non-OAB patients. This technology may potentially streamline the diagnosis of OAB and identify localized areas of increased DO for targeted treatment.
Authors
- Lay Guat Ng (ORCID: https://orcid.org/0000-0002-3073-5396)
- Mark K. F. Wong
- Jin Yong (ORCID: https://orcid.org/0000-0002-1544-2042)
- Ajith M. Joseph (ORCID: https://orcid.org/0000-0003-2001-9465)
- E. C. Loh
- Yu Guang Tan (ORCID: https://orcid.org/0000-0002-8166-0582)
- Shauna J. Q. Woo
Institutions
- Singapore General Hospital (SG)
Publication Details
- Journal
- Neurourology and Urodynamics
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1002/nau.70040
- Citations
- 1
- Primary Topic
- Urinary Bladder and Prostate Research
- Type
- article
- Field-Weighted Citation Impact
- 1.84