Machine learning algorithms predict breast cancer incidence risk: a data-driven retrospective study based on biochemical biomarkers
Our study identified two biochemical biomarkers (GGT and ALT) as promising indicators for breast cancer prediction. Incorporating these findings into a tailored breast cancer risk prediction model is needed in our future research.
Authors
- Peng Wu (ORCID: https://orcid.org/0000-0003-2026-4102)
- Junhao He (ORCID: https://orcid.org/0009-0000-3126-8868)
- Qianqian Guo (ORCID: https://orcid.org/0000-0001-6360-9911)
- Ge Zhang (ORCID: https://orcid.org/0000-0002-7807-7695)
- Wu Zhou (ORCID: https://orcid.org/0000-0002-9202-1989)
- Qianjun Chen (ORCID: https://orcid.org/0000-0001-6761-7740)
Institutions
- Guangzhou University of Chinese Medicine (CN)
- Hong Kong Baptist University (HK)
- Northwestern Polytechnical University (CN)
- Macronix International (China) (CN)
- Guangdong Provincial Hospital of Traditional Chinese Medicine (CN)
- South China University of Technology (CN)
Publication Details
- Journal
- BMC Cancer
- Published
- 2025-07-01
- DOI
- https://doi.org/10.1186/s12885-025-14444-x
- Citations
- 5
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 12.40
Funders
- National Natural Science Foundation of China
- Guangzhou Municipal Science and Technology Project