Predictive model of prognosis index for invasive micropapillary carcinoma of the breast based on machine learning: a SEER population-based study
A machine learning model for IMPC in patients with breast cancer was developed to estimate the 5-year OS. The XGBoost model had a promising performance and can help clinicians determine the early prognosis of patients with IMPC; therefore, the model can improve clinical outcomes by influencing management strategies and patient health care decisions.
Authors
- Chuangui Song (ORCID: https://orcid.org/0000-0002-3384-0634)
- Yushuai Yu (ORCID: https://orcid.org/0009-0002-2494-4981)
- Kaiyan Huang (ORCID: https://orcid.org/0009-0005-1635-9354)
- Xin Yu (ORCID: https://orcid.org/0009-0006-6581-2204)
- Qing Wang (ORCID: https://orcid.org/0000-0002-9855-4348)
- Mingyao Huang (ORCID: https://orcid.org/0000-0003-3446-2169)
- Zirong Jiang
Institutions
- Fujian Medical University (CN)
- Ningde Normal University (CN)
- Fujian Provincial Cancer Hospital (CN)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2024-09-27
- DOI
- https://doi.org/10.1186/s12911-024-02669-y
- Citations
- 5
- Primary Topic
- Breast Cancer Treatment Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.43