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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...
Autores principales: | Rendleman, Michael C., Buatti, John M., Braun, Terry A., Smith, Brian J., Nwakama, Chibuzo, Beichel, Reinhard R., Brown, Bart, Casavant, Thomas L. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
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 |
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