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Exploring the ability of natural language processing to extract data from nursing narratives.

机译:探索自然语言处理从护理叙事中提取数据的能力。

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摘要

Natural Language Processing (NLP) offers an approach for capturing data from narratives and creating structured reports for further computer processing. We explored the ability of a NLP system, Medical Language Extraction and Encoding (MedLEE), on nursing narratives. MedLEE extracted 490 concepts from narrative text in a sample of 553 oncology nursing process notes. The most frequently monitored and recorded signs and symptoms were related to chemotherapy care, such as adverse reactions, shortness of breath, nausea, pain, and bleeding. In terms of nursing interventions, chemotherapy, blood culture, medication, and blood transfusion were commonly recorded in free text. NLP may provide a feasible approach to extract data related to patient safety/quality measures and nursing outcomes by capturing nursing concepts that are not recorded through structured data entry. For better NLP performance in the domain of nursing, additional nursing terms and abbreviations must be added to MedLEE's lexicon.
机译:自然语言处理(NLP)提供了一种从叙述中捕获数据并创建结构化报告以进行进一步计算机处理的方法。我们探索了NL​​P系统,医疗语言提取和编码(MedLEE)在护理叙事上的能力。 MedLEE从553份肿瘤学护理过程注释样本中的叙述文本中提取了490个概念。监测和记录最频繁的体征和症状与化疗相关,例如不良反应,呼吸急促,恶心,疼痛和出血。在护理干预方面,化学疗法,血液培养,药物治疗和输血通常记录在自由文本中。 NLP可以通过捕获未通过结构化数据输入记录的护理概念,提供一种可行的方法来提取与患者安全/质量措施和护理结果相关的数据。为了在护理领域获得更好的NLP性能,必须在MedLEE的词典中添加其他护理术语和缩写。

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