关于人工智能,机器和医学深度学习的研究:全球特征,准备和公平性
Doris Klingelhöfer1, Markus Braun2, Janis Dröge2
1Institute of Occupational, Social and Environmental Medicine, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany. klingelhoefer@med.uni-frankfurt.de.
Globalization and health
|June 8, 2025
概括
医学领域的人工智能 (AI) 研究正在快速增长,顶级经济体处于领先地位. 全球合作对于确保公平的人工智能发展和防止差距至关重要.
科学领域:
- 医学研究 医学研究
- 医疗保健创新 医疗保健创新
- 人工智能应用的人工智能应用.
背景情况:
- 人工智能 (AI) 准备改变医学研究和医疗保健.
- 人工智能在医学中的采用伴随着重大风险和道德问题.
- 迫切需要科学证据来指导AI的开发和实施.
研究的目的:
- 分析医学 (AImed) 研究中人工智能的全球趋势和差异.
- 确定影响人工智能研究成果和参与的社会经济因素.
- 为公平的全球人工智能发展策略提供信息.
主要方法:
- 在AImed中对时间和地理出版模式的分析.
- 评估国家对人工智能接入的准备和社会经济条件.
- 检查出版物输出,引用模式和经济/创新指标.
主要成果:
- 自2017年以来,人工智能出版物的大幅增加,以美国,中国,英国,德国和韩国为首.
- 人工智能出版物输出和经济/创新指标之间存在强烈的相关性.
- 与全球北方相比,全球南方国家在人工智能研究方面面临着劣势,尽管一些国家显示出未来的潜力.
结论:
- 先进的全球网络对于公平的AI发展至关重要.
- 解决人工智能系统中的种族和地区不平等问题至关重要.
- 确保经济较弱国家的参与对于有益的AI实施至关重要.
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