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CancerSiamese: one-shot learning for predicting primary and metastatic tumor types unseen during model training
BACKGROUND: The state-of-the-art deep learning based cancer type prediction can only predict cancer types whose samples are available during the training where the sample size is commonly large. In this paper, we consider how to utilize the existing training samples to predict cancer types unseen du...
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| Опубликовано в: : | BMC Bioinformatics |
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| Главные авторы: | , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
BioMed Central
2021
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8117642/ https://ncbi.nlm.nih.gov/pubmed/33980137 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-021-04157-w |
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