在紧急医疗中对人工智能临床研究的文献分析分析
Önder Limon1, Başak Bayram2, Murat Çetin3
1Izmir University of Economics, Faculty of Medicine, IUE Medicalpoint Hospital, Izmir, Turkiye.
Medicine
|July 15, 2025
概括
人工智能 (AI) 和机器学习 (ML) 越来越多地用于紧急医疗. 这项研究分析了十年的文献,揭示了越来越多的研究趋势和紧急护理人工智能应用中的关键主题.
科学领域:
- 图书统计学 图书统计学
- 医疗信息学 医疗信息学
- 紧急医疗研究 紧急医疗研究
背景情况:
- 人工智能 (AI) 和机器学习 (ML) 的快速进步为改善医疗保健提供了巨大的潜力.
- 应急部门 (ED) 面临着独特的挑战,因为它们的快节奏和资源有限的性质,使它们适合AI集成.
- 在ED中的人工智能应用可以提高诊断准确度和优化患者护理,需要对现有的科学文献进行审查.
研究的目的:
- 在过去十年 (2015-2024) 中,系统地识别和描述AI和ML在紧急医疗中的应用的科学文献.
- 分析出版趋势,研究主题和该领域的关键贡献因素.
- 提供对当前情景和人工智能在紧急护理中的未来方向的见解.
主要方法:
- 使用Web of Science数据库进行了全面的文献识别搜索.
- 关键词"人工智能"或"机器学习"在"紧急医疗"类别中用于2015年至2024年间发表的文章.
- 分析包括描述性统计,引用数量,来源国,期刊发行,关键词聚类和主题映射.
主要成果:
- 总共分析了321篇文章,平均每篇文章引用10.04次,年增长率为37.87%.
- 美国是出版物的主要来源国,主要期刊包括复苏和美国紧急医疗杂志.
- 2024年的热门话题包括"健康",十年来"护理"是最受欢迎的. 顶级的利基主题是"医疗"",数字化转型"",教育"",数据库"和"紧急护理系统".
结论:
- 图书统计分析证实了AI和ML在紧急医疗研究中的重要和日益增长的作用.
- 这些发现揭示了当前的研究轨迹,并确定了紧急护理人工智能应用中的重点领域.
- 这项研究对研究人员和从业人员来说是一个有价值的资源,为这个快速发展的领域的未来调查提供信息.
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