研究热点和深度学习在重症监护医学的趋势:一个图书识别和可视化研究
Kaichen Zhang1, Yihua Fan1, Kunlan Long1
1Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, People's Republic of China.
Journal of multidisciplinary healthcare
|August 4, 2023
概括
在重症监护医学的深度学习正在迅速扩大,研究重点是疾病分类和患者结果预测. 需要进一步的合作,将这些先进的模型纳入临床实践.
科学领域:
- 关键护理医学 关键护理医学
- 人工智能的人工智能
- 图书统计学 图书统计学
背景情况:
- 深度学习 (DL) 在重症监护医学 (CCM) 的应用越来越多.
- 在CCM文献中缺乏对全球DL的全面的文献计量分析.
研究的目的:
- 系统地评估全球研究热点和CCM的DL趋势.
- 分析出版物输出,合作,引用和关键字的共同出现.
主要方法:
- 从科学网络的1708篇文章的图书统计分析.
- 使用了R软件 (Bibliometrix),微软Excel,VOSviewer和CiteSpace. 这三种软件.
主要成果:
- 在过去五年中,出版物激增 (95.67%).
- 中国和美国是主要的贡献者.
- 关键的研究领域包括疾病表型分类,早期恶化预测和预后预测.
- 常见的DL技术包括CNN,LSTM,RNN,变压器和注意力机制.
结论:
- 研究热点集中在疾病分类,早期预警和结果预测上.
- 加强合作研究对于开发用于CCM实践的强大的DL模型至关重要.
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