转化伦理和质量原则,以有效,安全和公平地开发,部署和使用人工智能技术在医疗保健
Nicoleta J Economou-Zavlanos1, Sophia Bessias1, Michael P Cary1,2
1Duke AI Health, Duke University School of Medicine, Durham, NC 27705, United States.
Journal of the American Medical Informatics Association : JAMIA
|November 30, 2023
概括
我们开发了一份实施指南,以标准化医疗保健中算法技术的评估,确保客观监督并促进更安全,更公平的AI. 本指南增强了在临床环境中对人工智能的可靠使用.
科学领域:
- 医疗保健技术评估 医疗保健技术评估
- 临床信息学是一种临床信息学.
- 医学中的人工智能
背景情况:
- 医疗保健中的算法技术带来了复杂的监管和监督挑战.
- 快速发展需要标准化的评估和治理框架.
- 确保健康AI中的伦理和质量原则对于可靠的实施至关重要.
研究的目的:
- 加强在临床护理和运营中对算法技术的机构评估和治理.
- 创建一个实施指南,标准化客观监督的评估标准.
- 促进开发更安全,更有效,更公平,更公平的算法.
主要方法:
- 开发了一个基于伦理和质量原则的框架:临床价值和安全,公平和公平,可用性和采用性,透明度和问责制以及监管合规性.
- 创建了评估算法技术的具体指南.
- 将框架和指导方针应用于不同生命周期阶段的四种不同的健康AI技术.
主要成果:
- 创建了一个实施指南,详细说明了可信的健康AI的评估标准和证据要求.
- 标准化的流程和明确的标准简化了监督和教育机构社区.
- 对四种技术的评估表明了实现更安全,更有效,更公平,更公平的算法实施的潜力.
结论:
- 开发了一个可扩展和适应的框架,将原则转化为可操作的评估标准.
- 该框架支持对算法技术在患者护理和医疗保健操作中的可靠实施.
- 标准化的评估流程改善了医疗保健环境中人工智能的治理.
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