Complex epilepsy phenotype extraction from narrative clinical discharge summaries.
Complex epilepsy phenotype extraction from narrative clinical discharge summaries.
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DOI：
10.1016/j.jbi.2014.06.006
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发表时间：
2014-10
影响因子：
4.5
通讯作者：
Zhang, Guo-Qiang
中科院分区：
文献类型：
--
作者：
Cui, Licong;Sahoo, Satya S.;Lhatoo, Samden D.;Garg, Gaurav;Rai, Prashant;Bozorgi, Alireza;Zhang, Guo-Qiang
癫痫是一种常见的严重神经系统疾病，具有一系列复杂的可能表型，从病理异常到脑电图变异。本文提出了一种称为癫痫表型提取 (PEEP) 的系统，用于从临床出院摘要中提取复杂的癫痫表型及其相关的解剖位置，临床出院摘要是此目的的主要数据源。 PEEP 通过将基于癫痫和癫痫本体论的命名实体识别方法嵌入到国家医学图书馆的 MetaMap 程序中，生成候选表型和解剖位置对。使用相关算法进一步处理此类候选对。导出的表型和相关位置已用于通过集成本体驱动的视觉查询界面进行队列识别。为了评估 PEEP 的性能，我们使用 400 份去识别化的出院摘要进行开发，另外 262 份用作测试数据。在提取癫痫表型方面，PEEP 的微平均精度为 0.924，召回率为 0.931，F1 测量值为 0.927。相关表型和解剖位置提取的性能显示微平均 F1 测量值为 0.856（精确度：0.852，召回率：0.859）。评估表明，PEEP 是提取复杂癫痫表型以进行队列识别的有效方法。
Epilepsy is a common serious neurological disorder with a complex set of possible phenotypes ranging from pathologic abnormalities to variations in electroencephalogram. This paper presents a system called Phenotype Exaction in Epilepsy (PEEP) for extracting complex epilepsy phenotypes and their correlated anatomical locations from clinical discharge summaries, a primary data source for this purpose. PEEP generates candidate phenotype and anatomical location pairs by embedding a named entity recognition method, based on the Epilepsy and Seizure Ontology, into the National Library of Medicine's MetaMap program. Such candidate pairs are further processed using a correlation algorithm. The derived phenotypes and correlated locations have been used for cohort identification with an integrated ontology-driven visual query interface. To evaluate the performance of PEEP, 400 de-identified discharge summaries were used for development and an additional 262 were used as test data. PEEP achieved a micro-averaged precision of 0.924, recall of 0.931, and F1-measure of 0.927 for extracting epilepsy phenotypes. The performance on the extraction of correlated phenotypes and anatomical locations shows a micro-averaged F1-measure of 0.856 (Precision: 0.852, Recall: 0.859). The evaluation demonstrates that PEEP is an effective approach to extracting complex epilepsy phenotypes for cohort identification.
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DOI：
10.1136/jamia.2009.001560
发表时间：
2010-09-01
影响因子：
6.4
作者：
Savova, Guergana K.;Masanz, James J.;Chute, Christopher G.
通讯作者：
Chute, Christopher G.
DOI：
10.1136/jamia.1994.95236146
发表时间：
1994-03-01
影响因子：
6.4
作者：
FRIEDMAN, C;ALDERSON, PO;JOHNSON, SB
通讯作者：
JOHNSON, SB
影响因子：
4.4
作者：
Sevenster, Merlijn;van Ommering, Rob;Qian, Yuechen
通讯作者：
Qian, Yuechen
影响因子：
2
作者：
JARO, MA
通讯作者：
JARO, MA
DOI：
10.1136/jamia.2009.002295
发表时间：
2010-05-01
影响因子：
6.4
作者：
Crowley, Rebecca S.;Castine, Melissa;Feldman, Michael
通讯作者：
Feldman, Michael