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使用本体将患者记录与临床试验相匹配

Matching Patient Records to Clinical Trials Using Ontologies
课程网址: http://videolectures.net/iswc07_cumc_mpr/  
主讲教师: Chintan Patel
开课单位: 哥伦比亚大学
开课时间: 2008-01-31
课程语种: 英语
中文简介:
本演讲描述了一个大型案例研究,探讨了本体推理对医学领域问题的适用性。我们调查是否有可能使用这样的推理来自动化目前劳动密集型和容易出错的临床任务,并将我们的案例研究集中在改进临床试验的队列选择上。使这些临床任务自动化的障碍是需要桥接原始患者数据(例如实验室测试或特定药物)与临床医生解释该数据的方式之间的语义鸿沟。我们的主要观点是,将患者与临床试验相匹配可以表达为语义检索的问题。我们描述了构建实际案例研究所面临的技术挑战,其中包括与可扩展性,大型本体集成以及处理嘈杂,不一致数据相关的问题。我们的解决方案基于SNOMED CT R本体,并可扩展至一年的患者记录(约240,000名患者)。
课程简介: This talk describes a large case study that explores the applicability of ontology reasoning to problems in the medical domain. We investigate whether it is possible to use such reasoning to automate com- mon clinical tasks that are currently labor intensive and error prone, and focus our case study on improving cohort selection for clinical trials. An obstacle to automating such clinical tasks is the need to bridge the semantic gulf between raw patient data, such as laboratory tests or specific medications, and the way a clinician interprets this data. Our key insight is that matching patients to clinical trials can be formulated as a problem of semantic retrieval. We describe the technical challenges to building a realistic case study, which include problems related to scalability, the integration of large ontologies, and dealing with noisy, inconsistent data. Our solution is based on the SNOMED CT R  ontology, and scales to one year of patient records (approx. 240,000 patients).
关 键 词: 医学领域; 临床试验; 语义检索
课程来源: 视频讲座网
最后编审: 2019-04-30:lxf
阅读次数: 71