Hierarchical Annotation for Building A Suite of Clinical Natural Language Processing Tasks: Progress Note Understanding
Hierarchical Annotation for Building A Suite of Clinical Natural Language Processing Tasks: Progress Note Understanding
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DOI：
10.48550/arxiv.2204.03035
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发表时间：
2022-04
期刊：
影响因子：
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通讯作者：
Yanjun Gao;Dmitriy Dligach;Timothy Miller;S. Tesch;Ryan Laffin;M. Churpek;M. Afshar
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文献类型：
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作者：
Yanjun Gao;Dmitriy Dligach;Timothy Miller;S. Tesch;Ryan Laffin;M. Churpek;M. Afshar
将自然语言处理方法应用于电子健康记录（EHR）数据引起了越来越多的兴趣。现有的语料库和标注集中在文本特征建模和关系预测上。然而，有一个注释的语料库建立临床诊断思维模型，涉及文本理解，领域知识抽象和推理的处理缺乏。在这项工作中，我们引入了一个层次化的注释模式，有三个阶段，以解决临床文本理解，临床推理和总结。我们创建了一个注释语料库的基础上收集了大量的公开可用的每日进展记录，一种类型的EHR，是时间敏感的，面向问题的，以及记录的主观，客观，评估和计划（SOAP）的格式。我们还定义了一套新的任务，进度说明理解，三个任务利用三个注释阶段。这个新套件旨在训练和评估未来的NLP模型，用于临床文本理解，临床知识表示，推理和总结。
Applying methods in natural language processing on electronic health records (EHR) data has attracted rising interests. Existing corpus and annotation focus on modeling textual features and relation prediction. However, there are a paucity of annotated corpus built to model clinical diagnostic thinking, a processing involving text understanding, domain knowledge abstraction and reasoning. In this work, we introduce a hierarchical annotation schema with three stages to address clinical text understanding, clinical reasoning and summarization. We create an annotated corpus based on a large collection of publicly available daily progress notes, a type of EHR that is time-sensitive, problem-oriented, and well-documented by the format of Subjective, Objective, Assessment and Plan (SOAP). We also define a new suite of tasks, Progress Note Understanding, with three tasks utilizing the three annotation stages. This new suite aims at training and evaluating future NLP models for clinical text understanding, clinical knowledge representation, inference and summarization.