Clinical prediction of pathological complete response in breast cancer: a machine learning study
The Naive Bayes model provides a robust tool for personalized treatment decisions in patients with breast cancer undergoing neoadjuvant therapy. By accurately predicting pCR rates, it enables clinicians to tailor treatment strategies, potentially improving outcomes.
Authors
- Tenghua Yu (ORCID: https://orcid.org/0000-0001-6346-8573)
- Liu Yang (ORCID: https://orcid.org/0000-0001-8174-1633)
- Chongwu He (ORCID: https://orcid.org/0009-0006-4510-944X)
- Longbo He
- Jing Chen (ORCID: https://orcid.org/0000-0001-5972-3623)
- Jin Zhu
Institutions
- First Affiliated Hospital of Jiangxi Medical College (CN)
- Jiangxi Provincial Cancer Hospital (CN)
- Jiangxi Provincial People's Hospital (CN)
Publication Details
- Journal
- BMC Cancer
- Published
- 2025-05-23
- DOI
- https://doi.org/10.1186/s12885-025-14335-1
- Citations
- 2
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 4.96
Funders
- National Natural Science Foundation of China
- Education Department of Jiangxi Province
- Health Commission of Jiangxi Province