Comparison of radiomics-based machine-learning classifiers for the pretreatment prediction of pathologic complete response to neoadjuvant therapy in breast cancer
Background Machine learning classifiers are increasingly used to create predictive models for pathological complete response (pCR) in breast cancer after neoadjuvant therapy (NAT). Few studies have compared the effectiveness of different ML classifiers. This study evaluated radiomics models based on...
| الحاوية / القاعدة: | PeerJ |
|---|---|
| المؤلفون الرئيسيون: | , , , , |
| التنسيق: | مقال |
| اللغة: | الإنجليزية |
| منشور في: |
PeerJ Inc.
2024-07-01
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://peerj.com/articles/17683.pdf |