在重症监护室的自然语言处理:范围审查
Julia K Pilowsky1,2,3, Jae-Won Choi1,4, Aldo Saavedra1,2
1Agency for Clinical Innovation, NSW Health, Australia.
概括
自然语言处理 (NLP) 在重症监护中越来越多地用于预测结果和识别条件等任务. 更广泛地采用这些人工智能技术可以加强临床研究和提高重症监护的质量.
科学领域:
- 人工智能的人工智能
- 临床信息学 临床信息学
- 自然语言处理自然语言处理.
背景情况:
- 重症监护室 (ICU) 产生大量的文本数据.
- 自然语言处理 (NLP) 应用在重症监护研究和质量改进中未得到充分利用.
- NLP为分析临床文本数据提供了潜力.
研究的目的:
- 审查NLP在重症监护专业中的当前应用.
- 促进对NLP在重症监护中的未来临床潜力的理解.
- 综合了近期在重症监护中的NLP研究结果.
主要方法:
- 使用了一个范围审查方法.
- 在PubMed数据库中对过去10年的文章进行了系统的搜索.
- 数据提取和叙事合成由独立审稿人进行.
主要成果:
- 八十七篇文章被纳入了审查.
- 最常见的NLP应用涉及预测临床结果 (例如死亡率) 和确定特定的临床概念 (例如败血症).
- 大多数研究集中在算法开发和内部验证上,临床实施有限.
结论:
- 在ICU中,NLP有多种应用,包括结果预测和概念识别.
- 提高临床医生对NLP技术的认识可以促进临床相关算法的开发.
- 在临床环境中进一步实施NLP工具是有必要的,以实现它们的全部潜力.
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