生成型人工智能,患者安全和医疗保健质量:一篇综述
1Google, Palo Alto, California, USA mdhowell@google.com.
BMJ quality & safety
|July 24, 2024
概括
人工智能 (AI) 的进步,特别是基础模型,为改善医疗保健质量和患者安全提供了新的途径. 这项技术可以解决长期存在的问题,尽管必须管理新的风险.
科学领域:
- 医疗保健技术 医疗保健技术 医疗保健技术
- 人工智能的人工智能
- 患者安全 患者安全
背景情况:
- 人工智能 (AI) 能力迅速发展,显示出影响医疗保健的巨大潜力.
- 传统的AI模型是特定任务的,限制了它们的应用.
- 基础模型代表着一种范式的转变,能够在没有特定任务培训的情况下处理各种各样的问题.
研究的目的:
- 提供基础模型的入门资料,包括它们的基本原则,好处和风险.
- 探索基础模型的潜力,以提高医疗保健质量和患者安全.
- 讨论先进的人工智能在医疗保健中带来的复杂性和新风险.
主要方法:
- 审查当前的人工智能能力,重点关注基础模型,生成AI和大型语言模型.
- 分析这些人工智能进步对医疗保健质量和患者安全挑战的适用性.
- 探索与在临床环境中实施先进AI相关的潜在好处,风险和未知因素.
主要成果:
- 基础模型代表了从单任务AI的显著演变,提供了更广泛的适用性.
- 这些先进的AI能力与提高医疗保健质量和患者安全有直接关系.
- 人工智能融入医疗保健引入了新的复杂性和潜在风险,需要仔细考虑.
结论:
- 基础模型和相关的人工智能技术已经准备好从根本上改变医疗保健提供.
- 人工智能显然有潜力解决医疗质量和患者安全方面的持续挑战.
- 进一步的研究和仔细的实施是必要的,以利用AI的好处,同时减轻其风险.
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