自然语言处理在护理研究中的应用:使用文本网络分析和主题建模的研究
Minji Mun1, Aeri Kim, Kyungmi Woo
1Author Affiliations: College of Nursing (Mrs Mun, Mrs Kim, and Dr Woo), and The Research Institute of Nursing Science, College of Nursing (Dr Woo), Seoul National University, South Korea.
Computers, informatics, nursing : CIN
|June 24, 2024
概括
护理研究中的自然语言处理 (NLP) 正在出现,其中的关键主题包括机器学习应用和健康结果. 通过NLP的整合,可以提高研究效率和护理质量.
科学领域:
- 护理科学 护理科学
- 信息学是一种信息学.
背景情况:
- 自然语言处理 (NLP) 在护理研究中的应用正在增长,但研究趋势和知识结构仍然不清楚.
- 了解这些趋势对于推进护理学术和有效整合NLP至关重要.
研究的目的:
- 揭示关于NLP的护理文献中的知识结构和研究趋势.
- 确定新兴的研究主题,并为未来的NLP在护理研究中的整合提供基础.
主要方法:
- 通过使用文本网络分析和主题建模,分析了443篇护理文献摘要.
- 核心关键字分析和主题建模是基于频率和中心性的.
主要成果:
- 出现了五个关键主题:术语识别和沟通,机器学习的应用,健康结果因素的探索,干预和参与者经验以及与疾病相关的算法.
- 确定了护理元范式的元素,有助于对护理元范式的更深入理解和扩展.
结论:
- 自然语言处理 (NLP) 在护理研究中处于早期阶段,但显示出提高研究效率和质量的潜力.
- 结果支持将NLP整合到护理科目中,验证护理的价值,并推进护理科学范式.
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