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Siamese neural networks for the classification of high-dimensional radiomic features
This study demonstrates that a variant of a Siamese neural network architecture is more effective at classifying high-dimensional radiomic features (extracted from T2 MRI images) than traditional models, such as a Support Vector Machine or Discriminant Analysis. Ninety-nine female patients, between...
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| Veröffentlicht in: | Proc SPIE Int Soc Opt Eng |
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| Hauptverfasser: | , , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
2020
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7288755/ https://ncbi.nlm.nih.gov/pubmed/32528215 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/12.2549389 |
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