Context-aware query design combines knowledge and data for efficient reading and reasoning
| Autor: | Emilee Holtzapple, Natasa Miskov-Zivanov, Brent H. Cochran |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0303 health sciences
Focus (computing) Biological data Information retrieval Computer science media_common.quotation_subject Context (language use) computer.software_genre 03 medical and health sciences Information extraction 0302 clinical medicine Differentially expressed genes 030220 oncology & carcinogenesis Reading (process) computer 030304 developmental biology media_common |
| Zdroj: | BioNLP@NAACL-HLT |
| DOI: | 10.18653/v1/2021.bionlp-1.26 |
| Popis: | The amount of biomedical literature has vastly increased over the past few decades. As a result, the sheer quantity of accessible information is overwhelming, and complicates manual information retrieval. Automated methods seek to speed up information retrieval from biomedical literature. However, such automated methods are still too time-intensive to survey all existing biomedical literature. We present a methodology for automatically generating literature queries that select relevant papers based on biological data. By using differentially expressed genes to inform our literature searches, we focus information extraction on mechanistic signaling details that are crucial for the disease or context of interest. |
| Databáze: | OpenAIRE |
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