PSOA-LSTM: a hybrid attention-based LSTM model optimized by particle swarm optimization for accurate lung cancer incidence forecasting in China (1990–2021)
The proposed PSOA-LSTM model outperforms benchmark models in predicting lung cancer incidence across demographic segments, offering a reliable decision-support tool for public health surveillance, early warning systems, and health policy formulation.
Authors
- Jianrong Dai (ORCID: https://orcid.org/0000-0002-1716-4058)
- Guang Yang (ORCID: https://orcid.org/0000-0002-2060-0500)
- Kun Zhu (ORCID: https://orcid.org/0000-0003-3030-9212)
- Nannan Xu (ORCID: https://orcid.org/0009-0008-9836-5193)
- Li Ming
Institutions
- Qiqihar Medical University (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-08-08
- DOI
- https://doi.org/10.3389/fmed.2025.1620257
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00