Forecasting Teleconsultation Demand Using an Ensemble CNN Attention-Based BILSTM Model with Additional Variables

To enhance the forecasting accuracy of daily teleconsultation demand, this study proposes an ensemble hybrid deep learning model. The proposed ensemble CNN attention-based BILSTM model (ECA-BILSTM) combines shallow convolutional neural networks (CNNs), attention mechanisms, and bidirectional long sh...

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Detalles Bibliográficos
Autores principales: Chen, Wenjia, Li, Jinlin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8391747/
https://www.ncbi.nlm.nih.gov/pubmed/34442130
http://dx.doi.org/10.3390/healthcare9080992

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8391747/
https://www.ncbi.nlm.nih.gov/pubmed/34442130
http://dx.doi.org/10.3390/healthcare9080992

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