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Graph Message Passing with Cross-location Attentions for Long-term ILI Prediction
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<span title="2019-12-29">2019</span>
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arXiv
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<span title="2019-12-21">2019</span>
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In this paper, we design a cross-location attention based graph neural network (Cola-GNN) for learning time series embeddings and location aware attentions. ...
The proposed method shows strong predictive performance and leads to interpretable results for long-term epidemic predictions. ...
Model Complexity
Conclusion In this work, we propose a graph-based deep learning framework with cross-location attentions to study the spatiotemporal influence of long-term epidemiological predictions ...
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Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting
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<span title="2020-11-23">2020</span>
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arXiv
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<span title="2020-10-27">2020</span>
<span class="release-stage" >pre-print</span>
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We implement multiple recurrent neural network-based deep learning models and combine them using the stacking ensemble technique. ...
Deep learning-based time series models for forecasting have recently gained popularity and have been successfully used for epidemic forecasting. ...
ACKNOWLEDGMENT The authors would like to thank members of the Biocomplexity COVID-19 Response Team and Network Systems Science and Advanced Computing (NSSAC) Division for their thoughtful comments and ...
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Applications of Technological Solutions in Primary Ways of Preventing Transmission of Respiratory Infectious Diseases—A Systematic Literature Review
<span title="2021-10-14">2021</span>
<i title="MDPI AG">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vyslcn4ljzdq3jes5w7fln3qyu" style="color: black;">International Journal of Environmental Research and Public Health</a>
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Topics for further research and improvement were also identified such as the need for a better description of data analysis and evidence. ...
Findings showed a greater trend in studies related to pandemic planning and, among the support mechanisms adopted, data and mathematical application-related solutions received greater attention. ...
S48
[77]
Cola-GNN: Cross-location Attention based
Graph Neural Networks for Long-term ILI
Prediction
Cross-location attention-based graph
neural network for learning time
series embeddings ...
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<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/ijerph182010765">doi:10.3390/ijerph182010765</a>
<a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34682511">pmid:34682511</a>
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