Automated Detection of Presymptomatic Conditions in Spinocerebellar Ataxia Type 2 Using Monte Carlo Dropout and Deep Neural Network Techniques with Electrooculogram Signals

Application of deep learning (DL) to the field of healthcare is aiding clinicians to make an accurate diagnosis. DL provides reliable results for image processing and sensor interpretation problems most of the time. However, model uncertainty should also be thoroughly quantified. This paper therefor...

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Detalles Bibliográficos
Autores principales: Stoean, Catalin, Stoean, Ruxandra, Atencia, Miguel, Abdar, Moloud, Velázquez-Pérez, Luis, Khosravi, Abbas, Nahavandi, Saeid, Acharya, U. Rajendra, Joya, Gonzalo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309035/
https://www.ncbi.nlm.nih.gov/pubmed/32471077
http://dx.doi.org/10.3390/s20113032

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309035/
https://www.ncbi.nlm.nih.gov/pubmed/32471077
http://dx.doi.org/10.3390/s20113032

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