Prediction of outpatient visits for allergic rhinitis using an artificial intelligence LSTM model - a study in Eastern China
The model presented here could effectively predict the daily outpatient visits for allergic rhinitis patients based on air pollution and meteorological data, thereby offering valuable data-driven support for hospital management and for potentially improving societal management and prevention of allergic rhinitis.
Authors
- Wei Tang (ORCID: https://orcid.org/0000-0002-7529-3608)
- Xiaofeng Fan (ORCID: https://orcid.org/0000-0001-6288-4866)
- Yongran Cheng (ORCID: https://orcid.org/0000-0003-2646-560X)
- Sirui Wang (ORCID: https://orcid.org/0000-0002-0014-2979)
- S.M Liu (ORCID: https://orcid.org/0000-0002-5522-3901)
- Liwei Chen (ORCID: https://orcid.org/0000-0002-8458-5661)
- Mingwei Wang (ORCID: https://orcid.org/0000-0001-9060-5107)
- Lixia Sun
- Lili Dai (ORCID: https://orcid.org/0000-0002-9294-5719)
- Kaijie Li (ORCID: https://orcid.org/0009-0005-0681-5512)
- Jie Wang (ORCID: https://orcid.org/0000-0002-9937-2351)
Institutions
- Hangzhou Normal University (CN)
- Hangzhou Xixi hospital (CN)
- Zhejiang University of Water Resource and Electric Power (CN)
Publication Details
- Journal
- BMC Public Health
- Published
- 2025-04-09
- DOI
- https://doi.org/10.1186/s12889-025-22430-y
- Citations
- 1
- Primary Topic
- Allergic Rhinitis and Sensitization
- Type
- article
- Field-Weighted Citation Impact
- 1.62
Funders
- Hangzhou Normal University