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Patient similarity by joint matrix trifactorization to identify subgroups in acute myeloid leukemia
OBJECTIVE: Computing patients’ similarity is of great interest in precision oncology since it supports clustering and subgroup identification, eventually leading to tailored therapies. The availability of large amounts of biomedical data, characterized by large feature sets and sparse content, motiv...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6951984/ https://www.ncbi.nlm.nih.gov/pubmed/31984320 http://dx.doi.org/10.1093/jamiaopen/ooy008 |