关于数据驱动健康应用中的负责任人工智能解决方案的全球视角
Jessica Rudd1, Claudia Igbrude2
1Atlanta, GA USA.
概括
全球医疗保健人工智能发展必须优先考虑边缘化社区,并解决数据,监管和基础设施挑战,以实现全球公平的患者结果. 这确保了人工智能有利于所有人群.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 全球卫生平等全球卫生平等
背景情况:
- 医疗保健人工智能对全球接入,护理质量和患者结果具有变革潜力.
- 当前的人工智能发展往往忽视了全球多样化的需求,特别是边缘化社区的需求.
- 对医疗应用的专注审查为面临发展挑战的技术人员提供了背景.
研究的目的:
- 审查数据,人工智能技术设计,监管和全球医疗保健人工智能部署基础设施方面的挑战.
- 突出导致数据缺口,监管障碍和连接问题的因素.
- 强调在开发医疗保健人工智能方面需要全球视角.
主要方法:
- 文献综述专注于医学AI应用.
- 分析数据可用性和质量的挑战.
- 审查监管格局和基础设施限制 (电力,网络).
主要成果:
- 医疗保健数据存在重大差距,特别是在边缘化群体.
- 监管框架和基础设施 (电力,网络连接) 构成了全球人工智能部署的主要障碍.
- 医疗保健和教育的社会体系不足进一步阻碍了普遍的人工智能影响.
结论:
- 发展全球医疗保健人工智能需要采取积极的方法来解决数据,监管和基础设施差异.
- 优先考虑边缘化社区和全球视角对于公平的人工智能解决方案至关重要.
- 为开发原型AI提供了建议,以更好地满足全球人口的需求.
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