A preoperative predictive model based on multi-modal features to predict pathological complete response after neoadjuvant chemoimmunotherapy in esophageal cancer patients
The combined multi-modality model we propose can better predict the pCR status of esophageal cancer and help inform clinical treatment decisions.
Authors
- Liting Shi (ORCID: https://orcid.org/0000-0002-7771-2001)
- Lin Cai (ORCID: https://orcid.org/0000-0003-3146-2251)
- Hui Zhu (ORCID: https://orcid.org/0000-0002-6629-019X)
- Ge Song (ORCID: https://orcid.org/0009-0001-8359-7687)
- Yanran Hu (ORCID: https://orcid.org/0000-0002-5188-1851)
- Yana Qi (ORCID: https://orcid.org/0000-0003-4287-7348)
Institutions
- Zhejiang Chinese Medical University (CN)
- Chinese Academy of Sciences (CN)
- Zhejiang Cancer Hospital (CN)
- Shandong Tumor Hospital (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2025-01-27
- DOI
- https://doi.org/10.3389/fimmu.2025.1530279
- Citations
- 12
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 14.96
Funders
- Natural Science Foundation of Shandong Province
- Science and Technology Program of Zhejiang Province