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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...
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| Publicado no: | JAMIA Open |
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| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6951984/ https://ncbi.nlm.nih.gov/pubmed/31984320 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamiaopen/ooy008 |
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