Combining multi-level evidence for medical record retrieval

Dongqing Zhu, Ben Carterette
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引用次数: 22

Abstract

The increasing prevalence of electronic health records containing rich information about a patient's health and physical condition has the potential to transform research in health and medicine. In this work, we present a health record search system for finding patients matching certain inclusion criteria (specified as keyword queries) for clinical studies. In particular, our system aggregates multi-level evidence and combines proven statistical IR models, both in an innovative way, and achieves a 20% MAP (mean average precision) improvement over a strong baseline. Moreover, our cross-validation results show that the overall performance of our system is comparable to other top-performing systems on the same task.
结合多层次证据进行病历检索
包含有关病人健康和身体状况的丰富信息的电子健康记录日益普及,有可能改变健康和医学研究。在这项工作中,我们提出了一个健康记录搜索系统,用于查找符合临床研究的某些纳入标准(指定为关键字查询)的患者。特别是,我们的系统以创新的方式汇集了多层次的证据,并结合了经过验证的统计IR模型,并在强基线的基础上实现了20%的MAP(平均精度)提高。此外,我们的交叉验证结果表明,在相同的任务上,我们的系统的整体性能与其他性能最好的系统相当。
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