A recurrence model for non-puerperal mastitis patients based on machine learning
The machine learning model developed in this study, serving as an effective tool for predicting NPM recurrence, aids doctors in making more individualized treatment decisions, thereby enhancing therapeutic efficacy and reducing the risk of recurrence.
Authors
- Xijing Fan
- Zhaoxia Wu (ORCID: https://orcid.org/0000-0001-6230-7452)
- Feng Dong (ORCID: https://orcid.org/0000-0001-7091-2169)
- Lingling Zhang (ORCID: https://orcid.org/0000-0002-9161-4387)
- Qian Yu
- G. Li
- Yu Ying (ORCID: https://orcid.org/0000-0001-5157-4053)
Institutions
- Zhejiang Chinese Medical University (CN)
- Shandong Maternal and Child Health Hospital (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-01-16
- DOI
- https://doi.org/10.1371/journal.pone.0315406
- Primary Topic
- Breast Lesions and Carcinomas
- Type
- article
- Field-Weighted Citation Impact
- 0.00