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EXTRACTING SEMANTIC PREDICATIONS FROM MEDLINE CITATIONS FOR PHARMACOGENOMICS

机译:从MEDLINE引用中提取药物遗传组学的语义预测

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We describe a natural language processing system (Enhanced SemRep) to identify core assertions on pharmacogenomics in Medline citations. Extracted information is represented as semantic predications covering a range of relations relevant to this domain. The specific relations addressed by the system provide greater precision than that achievable with methods that rely on entity co-occurrence. The development of Enhanced SemRep is based on the adaptation of an existing system and crucially depends on domain knowledge in the Unified Medical Language System. We provide a preliminary evaluation (55% recall and 73% precision) and discuss the potential of this system in assisting both clinical practice and scientific investigation.
机译:我们描述了一种自然语言处理系统(Enhanced SemRep),以识别Medline引用中药物基因组学的核心主张。提取的信息表示为语义谓词,涵盖与此领域相关的一系列关系。与依赖实体共现的方法相比,该系统解决的特定关系提供的精度更高。增强型SemRep的开发基于现有系统的改编,并且至关重要地取决于统一医学语言系统中的领域知识。我们提供了初步评估(55%的查全率和73%的准确性),并讨论了该系统在协助临床实践和科学研究方面的潜力。

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