探索电子健康记录的全部潜力:用于临床实践的自然语言处理的应用
Liesbet Van Bulck1, Meghan Reading Turchioe2, Maxim Topaz2
1KU Leuven Department of Public Health and Primary Care, KU Leuven-University of Leuven, Kapucijnenvoer 7 PB7001, 3000 Leuven, Belgium.
European journal of cardiovascular nursing
|June 24, 2024
概括
自然语言处理 (NLP) 可以从电子健康记录 (EHR) 中的非结构化文本中解锁洞察力. 这项技术为心血管护理和临床实践提供了巨大的潜力.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能的人工智能
- 自然语言处理自然语言处理.
背景情况:
- 电子健康记录 (EHR) 包含大量的患者数据.
- 大多数EHR数据是非结构化的文本,限制了其分析潜力.
- 自然语言处理 (NLP) 提供了一种解释非结构化临床文本的方法.
研究的目的:
- 探索NLP在医疗保健中的应用.
- 突出NLP在心血管护理中的潜力.
- 引导临床医生实施NLP.
主要方法:
- 讨论各种NLP技术.
- 审查NLP在分析临床文本方面的能力.
- 对临床医生实践NLP采用的指导.
主要成果:
- NLP可以从非结构化的EHR数据中提取有价值的患者信息.
- 在推进心血管护理研究和实践方面,NLP具有前途.
- 临床医生可以使用现有资源开始使用NLP工具.
结论:
- NLP是利用非结构化EHR数据的强大工具.
- 实施NLP可以提高心血管护理中的患者护理和临床决策.
- 鼓励临床医生进一步探索和采用NLP.
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