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Robust Collaborative Clustering of Subjects and Radiomic Features for Cancer Prognosis
Feature dimensionality reduction plays an important role in radiomic studies with a large number of features. However, conventional radiomic approaches may suffer from noise, and feature dimensionality reduction techniques are not equipped to utilize latent supervision information of patient data un...
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| Pubblicato in: | IEEE Trans Biomed Eng |
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| Autori principali: | , , , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8048106/ https://ncbi.nlm.nih.gov/pubmed/31995474 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TBME.2020.2969839 |
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