An end-to-end interpretable machine-learning-based framework for early-stage diagnosis of gallbladder cancer using multi-modality medical data
The machine learning-based framework can effectively improve the accuracy of GBC diagnosis and is expected to have a more significant impact in other cancer diagnosis scenarios.
Authors
- Ziming Yin (ORCID: https://orcid.org/0000-0002-7572-1748)
- Yijun Shu (ORCID: https://orcid.org/0000-0001-6680-5678)
- Wei Gong
- Chuang Miao
- Xiangsong Wu
- Ziyi Yang (ORCID: https://orcid.org/0000-0001-9849-0180)
- Xiao Deng (ORCID: https://orcid.org/0009-0002-2041-3905)
- Haiying Zhao
- Weiwen Zou
- Yidi Zhu
Institutions
- University of Shanghai for Science and Technology (CN)
- XinHua Hospital (CN)
- Ministry of Education (CL)
Publication Details
- Journal
- BMC Cancer
- Published
- 2025-07-16
- DOI
- https://doi.org/10.1186/s12885-025-14462-9
- Citations
- 5
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 6.80
Funders
- National Natural Science Foundation of China
- Shanghai Jiao Tong University