Filtered selection coupled with support vector machines generate a functionally relevant prediction model for colorectal cancer

PURPOSE: There has been considerable interest in using whole-genome expression profiles for the classification of colorectal cancer (CRC). The selection of important features is a crucial step before training a classifier. METHODS: In this study, we built a model that uses support vector machine (SV...

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Detalles Bibliográficos
Autores principales: Gabere, Musa Nur, Hussein, Mohamed Aly, Aziz, Mohammad Azhar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2016
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4898422/
https://www.ncbi.nlm.nih.gov/pubmed/27330311
http://dx.doi.org/10.2147/OTT.S98910

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4898422/
https://www.ncbi.nlm.nih.gov/pubmed/27330311
http://dx.doi.org/10.2147/OTT.S98910

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