基于医学,现在和未来的大型语言模型
Ziqing Su1,2, Guozhang Tang1,3, Rui Huang1,2
1Department of Neurosurgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022 P.R. China.
Cellular and molecular bioengineering
|October 7, 2024
概括
大型语言模型 (LLM) 在医学上表现有前途,有助于教育,研究和临床实践. 然而,道德考虑和潜在的偏见需要仔细实施和政策指导,以便在医疗保健中安全有效地整合人工智能.
科学领域:
- 医疗人工智能 医疗人工智能
- 在医疗保健中的自然语言处理.
- 数字健康数字健康
背景情况:
- 大型语言模型 (LLM) 是先进的AI系统,能够理解和生成类似人类的文本.
- 像ChatGPT,GPT-3.5和GPT-4这样的LLM在医疗领域的整合既带来了机遇,也带来了挑战.
- 医疗保健专业人员和研究人员正在探索LLM在各种医疗领域的实用性.
研究的目的:
- 审查LLM在医学中的潜在应用,包括教育,研究,临床实践和护理.
- 鼓励在医疗保健机构负责任地采用LLM.
- 突出需要可访问的医疗人工智能工具,符合医疗保健标准.
主要方法:
- 对当前文献和医学领域LLM应用的新兴趋势进行全面的审查.
- 检查LLM对医学教育的影响 (课程设计,个性化学习,模拟).
- 分析科学研究 (写作,数据分析,实验设计),临床实践 (成像分析,决策支持,患者沟通) 和护理 (任务自动化,个性化护理,心理支持) 中的LLM角色.
主要成果:
- 在提高医学教育,简化研究流程,改善临床决策和优化护理工作流程方面,LLM显示出巨大的潜力.
- 在医学成像分析,患者教育和减少行政负担等领域显示的有效性.
- 确定的挑战包括道德复杂性,人工智能交互中的潜在缺乏同情心,以及偏见输出的风险.
结论:
- 当经过深思熟虑地实施时,LLM为推进医疗实践和研究提供了巨大的潜力.
- 解决道德问题,确保同情心和减轻偏见对于成功部署LLM至关重要.
- 进一步的研究和明确的政策指导方针对于安全有效地利用LLM在医疗保健中的好处至关重要.
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