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Toward Digital Staining using Imaging Mass Spectrometry and Random Forests

We show on Imaging Mass Spectrometry (IMS) data that the Random Forest classifier can be used for automated tissue classification and that it results in predictions with high sensitivities and positive predictive values, even when inter-sample variability is present in the data. We further demonstra...

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Detalhes bibliográficos
Main Authors: Hanselmann, Michael, Köthe, Ullrich, Kirchner, Marc, Renard, Bernhard Y., Amstalden, Erika R., Glunde, Kristine, Heeren, Ron M. A., Hamprecht, Fred A.
Formato: Artigo
Idioma:Inglês
Publicado em: 2009
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC2763415/
https://ncbi.nlm.nih.gov/pubmed/19469555
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1021/pr900253y
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