aEYE: A deep learning system for video nystagmus detection

BACKGROUND: Nystagmus identification and interpretation is challenging for non-experts who lack specific training in neuro-ophthalmology or neuro-otology. This challenge is magnified when the task is performed via telemedicine. Deep learning models have not been heavily studied in video-based eye mo...

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Detalles Bibliográficos
Autores principales: Wagle, Narayani, Morkos, John, Liu, Jingyan, Reith, Henry, Greenstein, Joseph, Gong, Kirby, Gangan, Indranuj, Pakhomov, Daniil, Hira, Sanchit, Komogortsev, Oleg V., Newman-Toker, David E., Winslow, Raimond, Zee, David S., Otero-Millan, Jorge, Green, Kemar E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Neurology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9403604/
https://www.ncbi.nlm.nih.gov/pubmed/36034311
http://dx.doi.org/10.3389/fneur.2022.963968

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9403604/
https://www.ncbi.nlm.nih.gov/pubmed/36034311
http://dx.doi.org/10.3389/fneur.2022.963968

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