Global burden and future trends of head and neck cancer: a deep learning-based analysis (1980–2030)
The current work offers a detailed analysis of the global burden of HNC based on the GBD 2021 dataset and demonstrates the accuracy of the HNCP-T model in predicting future trends. Significant regional and gender-based differences are found, with incidence rates rising, especially among women and in low-middle SDI regions. Furthermore, the results underscore the value of deep learning models in disease burden prediction, which can outperform traditional methods.
Authors
- Shuai Lv (ORCID: https://orcid.org/0000-0002-1154-3612)
- Jinyu Mei
- Xinyu Wang (ORCID: https://orcid.org/0009-0004-4974-9191)
- Wei Gong (ORCID: https://orcid.org/0000-0002-1527-3330)
- Linqiang Pan (ORCID: https://orcid.org/0000-0002-4554-455X)
- Qiancheng Hu
Institutions
- University of Science and Technology of China (CN)
- Anhui Medical University (CN)
- Second Affiliated Hospital of Anhui Medical University (CN)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-04-09
- DOI
- https://doi.org/10.1371/journal.pone.0320184
- Citations
- 9
- Primary Topic
- Global Cancer Incidence and Screening
- Type
- article
- Field-Weighted Citation Impact
- 9.41