Identifying Respiratory Findings in Emergency Department Reports for Biosurveillance using MetaMap
Identifying Respiratory Findings in Emergency Department Reports for Biosurveillance using MetaMap
复制标题
使用 MetaMap 识别急诊科生物监测报告中的呼吸系统检查结果
DOI：
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发表时间：
2004
期刊：
影响因子：
--
通讯作者：
Thomas C. Rindflesch
中科院分区：
文献类型：
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作者：
W. Chapman;M. Fiszman;J. Dowling;B. Chapman;Thomas C. Rindflesch
在患者口述报告中描述的临床条件对于自动检测呼吸系统疾病（如吸入性炭疽和肺炎）患者是必要的。我们将MetaMap应用于急诊科报告，提取出与检测下呼吸道暴发相关的71个临床条件。我们用MetaMap索引了急诊科报告中的UMLS术语，用专门的领域UMLS术语词典过滤了索引后的输出，并将感兴趣的临床状况映射到词典中的概念。我们将MetaMap准确识别病情的能力与医生的手册注释进行了比较，并评估了索引不正确的特征，以确定需要进行哪些额外处理。MetaMap识别临床状况的召回率为0.72，精度为0.56。MetaMap索引之外的必要处理包括查找验证、时间辨别、解剖位置辨别、查找疾病辨别和上下文推断。使用MetaMap成功识别急诊科报告中的临床状况需要针对感兴趣的临床问题的特定处理技术。
Clinical conditions described in patients' dictated reports are necessary for automated detection of patients with respiratory illnesses such as inhalational anthrax and pneumonia. We applied MetaMap to emergency department reports to extract a set of 71 clinical conditions relevant to detection of a lower respiratory outbreak. We indexed UMLS terms in emergency department reports with MetaMap, filtered the indexed output with a specialized lexicon of UMLS terms for the domain, and mapped the clinical conditions of interest to concepts in the lexicon. We compared MetaMap's ability to accurately identify the conditions against a physician's manual annotations and evaluated incorrectly indexed features to determine what additional processing is necessary. MetaMap identified the clinical conditions with a recall of 0.72 and a precision of 0.56. Necessary processing beyond MetaMap's indexing includes finding validation, temporal discrimination, anatomic location discrimination, finding-disease discrimination, and contextual inference. Successful identification of clinical conditions in an emergency department report with MetaMap requires processing techniques specific to the clinical question of interest.
使用混合语义/句法解析器的经验。
DOI：
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发表时间：
1995
期刊：
Proceedings. Symposium on Computer Applications in Medical Care
影响因子：
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作者：
Haug,PJ;Koehler,S;Lau,LM;Wang,P;Rocha,R;Huff,SM
通讯作者：
Huff,SM
DOI：
10.1016/j.ijbiomac.2021.01.138
发表时间：
2021-01-27
影响因子：
8.2
作者：
Tan, Beibei;Sun, Bolun;Yang, Wenge
通讯作者：
Yang, Wenge