361 Automated assessment of facial nerve function using multimodal machine learning
Objectives/Goals: Current popular scoring systems for evaluating facial nerve function are subjective and imprecise. This study aims to quantify speech and facial motor changes in patients suffering from facial palsy after cerebellopontine angle (CPA) tumor resection to lay the foundation for a scor...
Saved in:
| Main Authors: | Oren Wei, Diana Lopez, Ioan Lina, Kofi Boahene |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2025-04-01
|
| Series: | Journal of Clinical and Translational Science |
| Online Access: | https://www.cambridge.org/core/product/identifier/S2059866124009877/type/journal_article |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Automated Graphic Divergent Thinking Assessment: A Multimodal Machine Learning Approach
by: Hezhi Zhang, et al.
Published: (2025-04-01) -
Autologous Fat Grafting Improves Facial Nerve Function
by: Marco Klinger, et al.
Published: (2015-01-01) -
Investigating the Expression Level of Mir-361 in Patients with Breast Cancer
by: S Igder, et al.
Published: (2025-03-01) -
Selective Neurectomy of the Facial Nerve with Cross-Face Nerve Graft for Treating Postparalytic Facial Nerve Syndrome
by: Ko Nakao, et al.
Published: (2025-05-01) -
miR-361-5p contributes to the pathogenesis of Alzheimer’s disease
by: Abbas Jalaiei, et al.
Published: (2025-08-01)