A deep learning pipeline for detecting vestibular schwannoma patients with unilateral vestibular loss based on kinematic data.
Saved in:
| Title: | A deep learning pipeline for detecting vestibular schwannoma patients with unilateral vestibular loss based on kinematic data. |
|---|---|
| Authors: | Kohler Voinov LC; Department of Biomedical Engineering, Tsinghua University, Beijing, 100084, China., Sanchez-Manso S; Department of Biomedical Engineering, Tsinghua University, Beijing, 100084, China., Aryan R; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA., Millar JL; Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD, USA., Schubert MC; Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD, USA.; Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA., Cullen KE; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA. Kathleen.Cullen@jhu.edu.; Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA. Kathleen.Cullen@jhu.edu.; Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA. Kathleen.Cullen@jhu.edu.; Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, 21218, USA. Kathleen.Cullen@jhu.edu. |
| Source: | Scientific reports [Sci Rep] 2025 Nov 25; Vol. 15 (1), pp. 45343. Date of Electronic Publication: 2025 Nov 25. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| ISSN: | 2045-2322 |
|---|---|
| DOI: | 10.1038/s41598-025-29776-8 |
