Development of a Machine Learning Model Integrating Pathomics and Clinical Data to Predict Axillary Lymph Node Metastasis in Breast Cancer: A Two‐Center Study
Our study demonstrates the effectiveness of pathomics features in predicting ALNM in BC patients. Furthermore, the pathomics-based nomogram offers a valuable tool for personalized treatment planning in this patient population.
Authors
- Huan Zhang
- Fanli Qu (ORCID: https://orcid.org/0000-0002-6908-0630)
- Yangchao Luo (ORCID: https://orcid.org/0000-0002-0001-1194)
- Shanqi Li
- Long Wang (ORCID: https://orcid.org/0009-0009-8788-9116)
- Ping Wen (ORCID: https://orcid.org/0000-0002-3282-7083)
- Yulan Zhao (ORCID: https://orcid.org/0000-0002-9469-5119)
- Xuedong Yin (ORCID: https://orcid.org/0009-0004-1188-1525)
- Xiaohua Zeng
Institutions
- Chongqing University (CN)
- The Affiliated Yongchuan Hospital of Chongqing Medical University (CN)
- Chongqing Cancer Hospital (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- Cancer Reports
- Published
- 2025-08-31
- DOI
- https://doi.org/10.1002/cnr2.70302
- Primary Topic
- Breast Cancer Treatment Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Chongqing Municipal Health Commission
- Chongqing University
- Natural Science Foundation of Chongqing