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Hypotheses generation as supervised link discovery with automated class labeling on large-scale biomedical concept networks
Computational approaches to generate hypotheses from biomedical literature have been studied intensively in recent years. Nevertheless, it still remains a challenge to automatically discover novel, cross-silo biomedical hypotheses from large-scale literature repositories. In order to address this ch...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2012
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3394427/ https://www.ncbi.nlm.nih.gov/pubmed/22759614 http://dx.doi.org/10.1186/1471-2164-13-S3-S5 |