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Predictive performance of radiomic models based on features extracted from pretrained deep networks
OBJECTIVES: In radiomics, generic texture and morphological features are often used for modeling. Recently, features extracted from pretrained deep networks have been used as an alternative. However, extracting deep features involves several decisions, and it is unclear how these affect the resultin...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Springer Vienna
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733744/ https://www.ncbi.nlm.nih.gov/pubmed/36484873 http://dx.doi.org/10.1186/s13244-022-01328-y |