| Identifier |
20230312_nanos_posters_325 |
| Title |
Validating a Deep Learning System for Video Nystagmus Detection (aEYE) on NOVEL Eye Movement Recordings |
| Creator |
Preetham Bachina; Narayani Wagle; David Hale; Kemar Green |
| Affiliation |
(PB) (DH) Johns Hopkins University School of Medicine; (NW) Johns Hopkins University/Whiting School of Engineering; (KG) Johns Hopkins School of Medicine |
| Subject |
Ocular Motility; Nystagmus; Vestibular Disorders; Miscellaneous |
| Description |
aEYE is a deep learning system for video nystagmus detection that was developed from infrared video-oculography (VOG) videos of the right eye. The accuracy of aEYE on other VOG and non-VOG datasets is unknown. Understanding aEYE's generalizability on non-VOG datasets is of utmost importance. |
| Date |
2023-03-14 |
| Language |
eng |
| Format |
application/pdf |
| Type |
Text |
| Source |
2023 North American Neuro-Ophthalmology Society Annual Meeting |
| Relation is Part of |
NANOS Annual Meeting 2023: Poster Session II: Ocular Motility Disorders and Nystagmus |
| Collection |
Neuro-ophthalmology Virtual Education Library: NOVEL http://NOVEL.utah.edu |
| Publisher |
Spencer S. Eccles Health Sciences Library, University of Utah |
| Holding Institution |
North American Neuro-Ophthalmology Association. NANOS Executive Office 5841 Cedar Lake Road, Suite 204, Minneapolis, MN 55416 |
| Rights Management |
Copyright 2023. For further information regarding the rights to this collection, please visit: https://NOVEL.utah.edu/about/copyright |
| ARK |
ark:/87278/s627p1qy |
| Setname |
ehsl_novel_nam |
| ID |
2335530 |
| Reference URL |
https://collections.lib.utah.edu/ark:/87278/s627p1qy |
