低收入和中等收入国家的医疗保健数字化
Dominique J Monlezun1, Lillian Omutoko2, Patience Oduor3
1Division of Hospital Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN55905, United States of America (USA).
Bulletin of the World Health Organization
|January 30, 2025
概括
全球卫生安全面临非传染性疾病和多重危机的威胁,特别是影响低收入国家. 负责的人工智能 (AI) 支持的医疗数字化为全球可持续医疗保健系统提供了一个有希望的,公平的解决方案.
科学领域:
- 全球健康 全球健康
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 全球卫生安全受到不断增加的非传染性疾病,气候变化,债务和冲突的威胁,不成比例地影响低收入和中等收入国家 (LMICs).
- 低低收入国家面临着最高的疾病负担,医疗保健支出有限,加剧了健康不平等.
- 由人工智能 (AI) 和量子计算驱动的健康数字化为这些挑战提供了潜在的解决方案.
研究的目的:
- 批判性地分析管理,基础设施和安全支持者,以实现负责任的AI-enabled健康数字化.
- 探索公私伙伴关系,民主化主权人工智能和嵌入式人类安全的用例.
- 通过以人为中心,管理的战略竞争,提出加速全球健康的建议.
主要方法:
- 综合理论观点和学术界,工业界和实践中的实际经验,进行多部门的批判性分析.
- 检查关键推动因素:人工智能支持的健康数字化治理,基础设施和安全.
- 审查领先的使用案例,证明AI在全球健康进步中的作用.
主要成果:
- 负责的人工智能支持的数字化需要强大的治理,基础设施和安全框架,以实现公平的医疗保健.
- 公私伙伴关系和主权人工智能模型显示出民主化医疗技术的潜力.
- 以人为中心的方法对于推进人工智能加速的全球健康至关重要.
结论:
- 人工智能支持的健康数字化是加强全球卫生安全和实现可持续发展目标的重要策略.
- 解决治理,基础设施和安全的推动因素对于在LMIC中公平实施至关重要.
- 在知识交流和技术支持方面,LMIC和高收入国家之间的战略合作是必不可少的.
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