Breast cancer diagnosis through knowledge distillation of Swin transformer-based teacher–student models
Breast cancer is a significant global health concern, emphasizing the crucial need for a timely and accurate diagnosis to enhance survival rates. Traditional diagnostic methods rely on pathologists analyzing whole-slide images (WSIs) to identify and diagnose malignancies. However, this task is compl...
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| Autori principali: | , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
IOP Publishing
2023-01-01
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| Serie: | Machine Learning: Science and Technology |
| Soggetti: | |
| Accesso online: | https://doi.org/10.1088/2632-2153/ad10cc |
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