Machine Learning Models Based on Stretched-Exponential Diffusion Weighted Imaging to Predict TROP2 Expression in Nude Mouse Breast Cancer Models
Machine learning models based on SEM show promise for predicting TROP2 expression in breast cancer in nude mouse models. Among the models, XGBoost demonstrated outstanding performance, suggesting its potential for clinical applications.
Authors
- Yi Deng
- Jiali Liu (ORCID: https://orcid.org/0000-0002-8732-6139)
- Jiaming Ma (ORCID: https://orcid.org/0009-0003-4482-9355)
- Zhuo-han Wu
- Shou-yi Yang
- Chao-gang Han
- Zi-qin Deng
Institutions
- Shaoguan University (CN)
- Shaoguan Railway Hospital (CN)
Publication Details
- Journal
- Discovery Medicine
- Published
- 2025-01-01
- DOI
- https://doi.org/10.24976/discov.med.202537194.41
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36