人工智能,ChatGPT和其他大型语言模型用于健康的社会决定因素:当前状态和未来方向
Jasmine Chiat Ling Ong1, Benjamin Jun Jie Seng2, Jeren Zheng Feng Law3
1Division of Pharmacy, Singapore General Hospital, Singapore, Singapore; SingHealth Duke-NUS Medicine Academic Clinical Programme, Singapore, Singapore.
Cell reports. Medicine
|January 17, 2024
概括
解决健康的社会决定因素 (SDOH) 需要利用数字健康和人工智能. 必须克服诸如偏见和数字素养等挑战,以便在患者护理中公平地实施人工智能.
科学领域:
- 公共卫生 公共卫生
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 健康的社会决定因素 (SDOH) 显著影响患者的结果和健康公平.
- 由于COVID-19的流行,全球的健康不平等现象更加严重.
- 数字健康和人工智能为解决SDOH提供了潜在的解决方案.
研究的目的:
- 讨论数字健康和人工智能,包括大型语言模型 (LLM) 在解决SDOH方面的作用.
- 确定阻碍在医疗保健中公平采用人工智能的挑战.
- 为道德的人工智能开发和实施提出战略.
主要方法:
- 一个概括当前研究和发展的视角作品.
- 在SDOH的背景下广泛讨论数字健康,AI和LLMs.
- 分析与人工智能技术相关的挑战和风险.
主要成果:
- 数字健康和人工智能通过解决SDOH,为疾病监测和患者护理提供了变革性的机会.
- 存在重大挑战,包括数据标准化,基础设施,数字素养和算法偏见.
- 法律法规存在独特的风险,例如环境影响,偏见和错误信息.
结论:
- 作为一个SDOH,数字包容性的多层次方法至关重要.
- 开发全球道德和负责任的AI框架是必要的.
- 弥合人工智能开发和公平实施之间的差距对于改善健康结果至关重要.
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