Machine learning with the TCGA-HNSC dataset: improving usability by addressing inconsistency, sparsity, and high-dimensionality

BACKGROUND: In the era of precision oncology and publicly available datasets, the amount of information available for each patient case has dramatically increased. From clinical variables and PET-CT radiomics measures to DNA-variant and RNA expression profiles, such a wide variety of data presents a...

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Detalles Bibliográficos
Autores principales: Rendleman, Michael C., Buatti, John M., Braun, Terry A., Smith, Brian J., Nwakama, Chibuzo, Beichel, Reinhard R., Brown, Bart, Casavant, Thomas L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580485/
https://www.ncbi.nlm.nih.gov/pubmed/31208324
http://dx.doi.org/10.1186/s12859-019-2929-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580485/
https://www.ncbi.nlm.nih.gov/pubmed/31208324
http://dx.doi.org/10.1186/s12859-019-2929-8

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