PCovNet+: A CNN-VAE anomaly detection framework with LSTM embeddings for smartwatch-based COVID-19 detection

The world is slowly recovering from the Coronavirus disease 2019 (COVID-19) pandemic; however, humanity has experienced one of its According to work by Mishra et al. (2020), the study’s first phase included a cohort of 5,262 subjects, with 3,325 Fitbit users constituting the majority. However, among...

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Detalles Bibliográficos
Autores principales: Abir, Farhan Fuad, Chowdhury, Muhammad E.H., Tapotee, Malisha Islam, Mushtak, Adam, Khandakar, Amith, Mahmud, Sakib, Hasan, Anwarul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047244/
https://www.ncbi.nlm.nih.gov/pubmed/37006447
http://dx.doi.org/10.1016/j.engappai.2023.106130

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047244/
https://www.ncbi.nlm.nih.gov/pubmed/37006447
http://dx.doi.org/10.1016/j.engappai.2023.106130

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