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Multi-source Information Gain for Random Forest: An Application to CT Image Prediction from MRI Data
Random forest has been widely recognized as one of the most powerful learning-based predictors in literature, with a broad range of applications in medical imaging. Notable efforts have been focused on enhancing the algorithm in multiple facets. In this paper, we present an original concept of multi...
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| Pubblicato in: | Mach Learn Med Imaging |
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| Autori principali: | , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2015
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6261365/ https://ncbi.nlm.nih.gov/pubmed/30506065 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-319-24888-2_39 |
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