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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...
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| 主要な著者: | , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
BioMed Central
2012
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3394427/ https://ncbi.nlm.nih.gov/pubmed/22759614 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2164-13-S3-S5 |
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