弥合数字沟:在低资源环境中部署医疗人工智能技术的实用路线图
Evelyn Wong1, Alvaro Bermudez-Cañete2, Matthew J Campbell1
1School of Medicine, Stanford University, Stanford, California, USA.
Population health management
|February 3, 2025
概括
人工智能 (AI) 通过解决专业人员短缺问题,可以改善资源不足地区的医疗保健. 有效实施需要仔细规划基础设施,数据,培训和负责任的人工智能实践,以获得公平的机会.
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:
- 人工智能 (AI) 的整合正在改变医疗保健,诊断和治疗个性化.
- 由于医疗专业人员和资源的短缺,低资源环境面临着严重的医疗保健差异.
- 人工智能是一个有希望的途径来缓解这些差异,并改善服务不足地区的医疗保健机会.
研究的目的:
- 探索AI在低资源医疗环境中的实际部署.
- 确定AI工具在这些环境中有效和负责任地实施的关键因素.
- 提出一个可持续人工智能整合的框架,最大限度地降低风险,提高医疗保健的准入.
主要方法:
- 在低资源医疗保健环境中对人工智能的综合文献综述.
- 专家采访了医疗保健提供者,管理人员,AI开发人员和政府顾问.
- 分析实际部署的挑战和要求.
主要成果:
- 确定了成功部署人工智能的四个关键领域:基础设施,部署和数据管理,教育和培训以及负责任的人工智能实践.
- 强调需要具体的背景考虑,以解决公平护理的障碍.
- 强调了人工智能的潜力,以弥合因资源限制而加剧的医疗保健差距.
结论:
- 专注于基础设施,数据,培训和伦理考虑的结构化方法对于在低资源医疗保健中采用人工智能至关重要.
- 拟议的框架为可持续和公平的AI整合提供了指导,旨在改善服务不足的人群的健康结果.
- 应对实施挑战是实现人工智能在全球健康公平方面的全部潜力的关键.
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