Treatment decision support for esophageal cancer based on PET/CT data using deep learning
This study presents a novel hybrid deep learning architecture that enhances treatment decision support for esophageal cancer by leveraging multi-scale spatial encoding. The empirical evidence demonstrates that tailored architectural innovations significantly improve predictive accuracy over existing methods.
Authors
- Qiuxiang Zheng
- Fobao Lai
- Zhiyong Chen (ORCID: https://orcid.org/0000-0001-6766-0503)
Institutions
- Fujian Medical University (CN)
- First Affiliated Hospital of Fujian Medical University (CN)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2025-11-06
- DOI
- https://doi.org/10.1186/s12911-025-03223-0
- Primary Topic
- Esophageal Cancer Research and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00