Predicting breast cancer prognosis based on a novel pathomics model through CHEK1 expression analysis using machine learning algorithms
The novel pathomics model reliably predicted CHEK1 expression using machine learning algorithms, which might provide potential clinical utility for prognosis and treatment guidance.
Authors
- Rui Qu (ORCID: https://orcid.org/0000-0002-2716-6401)
- Libo Luo
- Huan Yue (ORCID: https://orcid.org/0000-0002-0482-511X)
- Xiaochi Hu (ORCID: https://orcid.org/0000-0001-7107-0573)
- Chen Chen (ORCID: https://orcid.org/0000-0003-1406-5721)
- Dan Gao (ORCID: https://orcid.org/0000-0002-0134-5030)
- Huijing Wang
Institutions
- First People’s Hospital of Zunyi (CN)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-05-09
- DOI
- https://doi.org/10.1371/journal.pone.0321717
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00