Real-Time Typical Urodynamic Signal Recognition System Using Deep Learning
DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.
Authors
- Xin Liu (ORCID: https://orcid.org/0000-0001-9901-9059)
- Ping Zhong (ORCID: https://orcid.org/0000-0003-4486-0013)
- Limin Liao (ORCID: https://orcid.org/0000-0002-7092-6576)
- Di Chen (ORCID: https://orcid.org/0009-0000-3863-7566)
Institutions
- Capital Medical University (CN)
- China Rehabilitation Research Center (CN)
Publication Details
- Journal
- International Neurourology Journal
- Published
- 2025-03-28
- DOI
- https://doi.org/10.5213/inj.2448430.215
- Citations
- 4
- Primary Topic
- Pelvic floor disorders treatments
- Type
- article
- Field-Weighted Citation Impact
- 6.67
Funders
- National Natural Science Foundation of China
- Key Technologies Research and Development Program