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Spatial Bayesian modeling of GLCM with application to malignant lesion characterization
The emerging field of cancer radiomics endeavors to characterize intrinsic patterns of tumor phenotypes and surrogate markers of response by transforming medical images into objects that yield quantifiable summary statistics to which regression and machine learning algorithms may be applied for stat...
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| Pubblicato in: | J Appl Stat |
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| Autori principali: | , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2018
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6706247/ https://ncbi.nlm.nih.gov/pubmed/31439980 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/02664763.2018.1473348 |
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