全球卫生诊所的大型语言模型:机遇和挑战
Satvik Tripathi1, Dana Alkhulaifat2, Meghana Muppuri3
1Center for Global and Population Health Research in Radiology, Department of Radiology, Perelman School of Medicine at University of Pennsylvania, Philadelphia, Pennsylvania; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
Journal of the American College of Radiology : JACR
|April 9, 2025
概括
大型语言模型 (LLM) 可以改变医疗保健沟通和研究. 解决诸如偏见和隐私等挑战对于公平的全球健康进步至关重要.
科学领域:
- 医疗保健中的人工智能
- 医疗信息学 医疗信息学
- 数字健康数字健康
背景情况:
- 大型语言模型 (LLM) 代表了人工智能的重大进步.
- 士课程有潜力彻底改变医疗保健沟通,研究和决策.
- 在医疗保健系统中LLMs的整合正在迅速发展.
研究的目的:
- 探索LLMs在医疗保健中的变革潜力.
- 确定与LLM在医疗保健中的实施相关的挑战.
- 为最大限度地提高LLM的好处,同时降低风险提出建议.
主要方法:
- 分析当前的LLM能力和在医疗保健中的应用.
- 确定包括数据偏见,隐私和数字素养在内的关键挑战.
- 对道德考虑和潜在解决方案的审查.
主要成果:
- 法律学显示出快速传播健康信息和克服语言障碍的巨大潜力.
- 挑战包括固有的数据偏见,隐私问题以及不同的数字素养水平.
- 士拥有强大的分析能力,能够为健康政策和临床实践提供信息.
结论:
- 士学位可以显著提升全球健康成果,促进健康公平.
- 开发强大的道德框架和偏见缓解策略是必不可少的.
- 需要采取教育举措,以确保全球范围内在医疗保健中公平获取和有效利用LLM.
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