A novel graph neural network based approach for influenza-like illness nowcasting: exploring the interplay of temporal, geographical, and functional spatial features
The incorporation of dual topology processing and the subsequent fusion mechanism allows the model to explore in-depth spatiotemporal feature interactions. Demonstrating superior performance, our approach shows great potential in early detection of flu trends for facilitating public health decisions and resource optimization.
Authors
- Yuxin He (ORCID: https://orcid.org/0000-0001-8857-9990)
- Yao-Qing Chen (ORCID: https://orcid.org/0000-0002-4659-1550)
- Xiaomao Fan (ORCID: https://orcid.org/0000-0001-8160-1294)
- Xiangjun Du (ORCID: https://orcid.org/0000-0001-8184-8430)
- Jiajia Luo (ORCID: https://orcid.org/0000-0002-9965-7664)
- Xuan Wang (ORCID: https://orcid.org/0000-0002-1381-8958)
- Yang Zhao (ORCID: https://orcid.org/0000-0003-1571-5394)
Institutions
- Sun Yat-sen University (CN)
- Shenzhen Technology University (CN)
Publication Details
- Journal
- BMC Public Health
- Published
- 2025-02-01
- DOI
- https://doi.org/10.1186/s12889-025-21618-6
- Citations
- 9
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 12.19
Funders
- Sun Yat-sen University