[Keyword Network Analysis and Topic Modeling of News Articles Related to Artificial Intelligence and Nursing].

IF 1 4区 医学 Q3 NURSING
Ju-Young Ha, Hyo-Jin Park
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引用次数: 1

Abstract

Purpose: The purpose of this study was to identify the main keywords, network properties, and main topics of news articles related to artificial intelligence technology in the field of nursing.

Methods: After collecting artificial intelligence-and nursing-related news articles published between January 1, 1991, and July 24, 2022, keywords were extracted via preprocessing. A total of 3,267 articles were searched, and 2,996 were used for the final analysis. Text network analysis and topic modeling were performed using NetMiner 4.4.

Results: As a result of analyzing the frequency of appearance, the keywords used most frequently were education, medical robot, telecom, dementia, and the older adults living alone. Keyword network analysis revealed the following results: a density of 0.002, an average degree of 8.79, and an average distance of 2.43; the central keywords identified were 'education,' 'medical robot,' and 'fourth industry.' Five topics were derived from news articles related to artificial intelligence and nursing: 'Artificial intelligence nursing research and development in the health and medical field,' 'Education using artificial intelligence for children and youth care,' 'Nursing robot for older adults care,' 'Community care policy and artificial intelligence,' and 'Smart care technology in an aging society.'

Conclusion: The use of artificial intelligence may be helpful among the local community, older adult, children, and adolescents. In particular, health management using artificial intelligence is indispensable now that we are facing a super-aging society. In the future, studies on nursing intervention and development of nursing programs using artificial intelligence should be conducted.

[关键词人工智能与护理相关新闻文章的网络分析与话题建模]。
目的:本研究的目的是识别护理领域人工智能技术相关新闻文章的主要关键词、网络属性和主要话题。方法:收集1991年1月1日至2022年7月24日期间发表的与人工智能和护理相关的新闻文章,通过预处理提取关键词。共检索了3267篇文章,其中2996篇用于最终分析。使用NetMiner 4.4进行文本网络分析和主题建模。结果:通过对出现频率的分析,出现频率最高的关键词为教育、医疗机器人、电信、痴呆、独居老年人。关键词网络分析结果表明:网络密度为0.002,平均程度为8.79,平均距离为2.43;确定的中心关键词是“教育”、“医疗机器人”和“第四产业”。“健康医疗领域的人工智能护理研究与开发”、“儿童和青少年护理领域的人工智能教育”、“老年人护理机器人”、“社区护理政策与人工智能”、“老龄化社会的智能护理技术”等5个主题来源于与人工智能和护理相关的新闻报道。结论:人工智能的使用可能对当地社区、老年人、儿童和青少年有帮助。特别是在超老龄化社会的今天,利用人工智能进行健康管理是必不可少的。未来还需开展人工智能护理干预研究和护理方案开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.30
自引率
13.30%
发文量
34
审稿时长
4-8 weeks
期刊介绍: Journal of Korean Academy of Nursing is published using an open access publication model. The journal welcomes original research on nursing intervention and health policies using appropriate research methods. Comprehensive review, concept analysis, and methodological papers are also welcome. The journal has a distinguished editorial board with extensive academic qualifications, ensuring that the journal maintains high scientific standards and has a broad international coverage.
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