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Fitbeat: COVID-19 estimation based on wristband heart rate using a contrastive convolutional auto-encoder

This study proposes a contrastive convolutional auto-encoder (contrastive CAE), a combined architecture of an auto-encoder and contrastive loss, to identify individuals with suspected COVID-19 infection using heart-rate data from participants with multiple sclerosis (MS) in the ongoing RADAR-CNS mHe...

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Detalles Bibliográficos
Autores principales: Liu, Shuo, Han, Jing, Puyal, Estela Laporta, Kontaxis, Spyridon, Sun, Shaoxiong, Locatelli, Patrick, Dineley, Judith, Pokorny, Florian B., Costa, Gloria Dalla, Leocani, Letizia, Guerrero, Ana Isabel, Nos, Carlos, Zabalza, Ana, Sørensen, Per Soelberg, Buron, Mathias, Magyari, Melinda, Ranjan, Yatharth, Rashid, Zulqarnain, Conde, Pauline, Stewart, Callum, Folarin, Amos A, Dobson, Richard JB, Bailón, Raquel, Vairavan, Srinivasan, Cummins, Nicholas, Narayan, Vaibhav A, Hotopf, Matthew, Comi, Giancarlo, Schuller, Björn, Consortium, RADAR-CNS
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8547790/
https://www.ncbi.nlm.nih.gov/pubmed/34720200
http://dx.doi.org/10.1016/j.patcog.2021.108403