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Cognitive computing for the automated extraction and meaningful use of health data in narrative medical notes: An application to the clinical management of hearing impaired aged patients

机译:在叙事医疗中的自动提取和有意义地使用健康数据的认知计算:临床管理的临床管理障碍年龄患者

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It is currently estimated that 80% of health data, such as that coming from medical transcripts, medical notes, lab results, email messages, attachments, is unstructured. Being unstructured, this information cannot be processed through automated PC procedures but requires the interpretation of human beings. We propose a cognitive computing system to extract automatically meaningful health information from the textual documents of the patient folder and merge this information into a structured data frame. The system was tested on the medical documents generated in an audiological outpatient hospital service; the data corpus consisted of the documents and reports generated longitudinally from the enrollment visit to the last available follow-up of hearing impaired aged patients treated with cochlear implants (CI). The system is based on an Information Extraction (IE) module to extract meaningful health information, a couple of ontologies to interpret the meaning and classify the extracted information into a logical hierarchy and an ad hoc developed structured data frame to gather the information. The system was designed to be compliant with the clinical best practices of the audiological/ENT (Ear-Nose-Throat) medical domains to ensure its ease of use in the real practice. The performance was assessed by measuring the percentage of information correctly extracted by the system against the one manual extracted by two experts. The accuracy of the system was very good (recall= 0.78; precision=3D0.95).
机译:目前估计80 %的健康数据,例如来自医疗成绩单,医疗说明,实验室结果,电子邮件,附件,附件是非结构化的。非结构化,无法通过自动PC程序处理此信息,但需要对人类的解释。我们提出了一种认知计算系统,可以从患者文件夹的文本文档中提取自动有意义的健康信息,并将该信息合并到结构化数据帧中。该系统在听力学门诊医院服务中产生的医疗文件上进行了测试;数据语料库由纵向生成的文件和报告组成,从入学访问中获取到有耳蜗植入物(CI)治疗的听力障碍患者的最后一次可用随访。该系统基于信息提取(IE)模块来提取有意义的健康信息,这是一种解释含义并将提取的信息分类为逻辑层次结构和ad Hoc开发的结构化数据帧来收集信息以收集信息。该系统旨在符合听力/耳鼻喉科(耳朵喉咙)医学领域的临床最佳实践,以确保其易于使用的实践。通过测量由系统正确提取的信息百分比对由两个专家提取的一项手动进行正确提取的信息百分比来评估性能。系统的准确性非常好(召回= 0.78; Precision = 3d0.95)。

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