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Sparse Contribution Feature Selection and Classifiers Optimized by Concave-Convex Variation for HCC Image Recognition
Accurate classification of hepatocellular carcinoma (HCC) image is of great importance in pathology diagnosis and treatment. This paper proposes a concave-convex variation (CCV) method to optimize three classifiers (random forest, support vector machine, and extreme learning machine) for the more ac...
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| Pubblicato in: | Biomed Res Int |
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| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Hindawi
2017
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5535756/ https://ncbi.nlm.nih.gov/pubmed/28798937 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2017/9718386 |
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