Deep learning models for hepatitis E incidence prediction leveraging Baidu index
Our experiments reveal a weak correlation and similar trends between the Baidu index and hepatitis E incidence. Baidu index proves to be valuable for predicting hepatitis E incidence. Furthermore, stack layers and KAN can also improve the representational ability of LSTM models.
Authors
- Yanhui Guo (ORCID: https://orcid.org/0000-0002-5444-3822)
- Shengnan Pang
- Yi Feng
- Xiya Cui
- Li Zhang (ORCID: https://orcid.org/0000-0002-3617-2627)
- Xuechen Zhao (ORCID: https://orcid.org/0009-0003-5002-8319)
Institutions
- Shandong Women’s University (CN)
- Shandong Center for Disease Control and Prevention (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- BMC Public Health
- Published
- 2024-10-31
- DOI
- https://doi.org/10.1186/s12889-024-20532-7
- Citations
- 4
- Primary Topic
- Hepatitis Viruses Studies and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 1.48
Funders
- Natural Science Foundation of Shandong Province