Interpretable deep learning for the remote characterisation of ambulation in multiple sclerosis using smartphones

The emergence of digital technologies such as smartphones in healthcare applications have demonstrated the possibility of developing rich, continuous, and objective measures of multiple sclerosis (MS) disability that can be administered remotely and out-of-clinic. Deep Convolutional Neural Networks...

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Detalles Bibliográficos
Autores principales: Creagh, Andrew P., Lipsmeier, Florian, Lindemann, Michael, Vos, Maarten De
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8275610/
https://www.ncbi.nlm.nih.gov/pubmed/34253769
http://dx.doi.org/10.1038/s41598-021-92776-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8275610/
https://www.ncbi.nlm.nih.gov/pubmed/34253769
http://dx.doi.org/10.1038/s41598-021-92776-x

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