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用言语彻底改变心脏病学:揭示医学科学中大型语言模型的影响写作

Abhijit Bhattaru¹, Naveena Yanamala², Partho P Sengupta²

¹Department of Cardiology, Rutgers Robert Wood Johnson Medical School and Robert Wood Johnson University Hospital, New Brunswick, New Jersey, USA; Department of Medicine, Rutgers New Jersey Medical School, Newark, New Jersey, USA.

The Canadian journal of cardiology

|June 1, 2024

概括

大型语言模型 (LLM) 为医学提供了强大的AI工具,帮助从数据分析到患者教育的任务. 然而,由于潜在的不准确性和缺乏原创性等局限性,人类监督至关重要.

科学领域:

人工智能在医学中的应用
机器学习应用机器学习应用
临床决策支持临床决策支持

背景情况:

大型语言模型 (LLM) 是现在商业上可用的先进机器学习工具.
临床实践和学术界越来越多地采用LLM来完成复杂的任务.
应用范围从逻辑文本处理到更高的认知功能.

研究的目的:

探索医学科学中LLMs的功能,机遇和限制.
专注于LLMs在心脏病领域的影响.
为了说明当前LLM技术在医疗保健中的能力和局限性.

主要方法:

对医学LLM应用的当前文献的综述.
在逻辑,管理和认知任务中分析LLM功能.
检查LLM在临床实践,医学教育和科学写作中的使用情况.

主要成果:

法律学在总结,编辑,统计分析和行政支持等任务中提供帮助.
在心脏病学中,LLM增强学习,管理电子病历,并为临床决策提供信息.
劳动法学改善了患者教育,并支持了同行评审过程.

结论:

士课程为推进医学科学和临床实践提供了重大机会.
诸如潜在的不准确性,抄袭和缺乏原创性等局限性需要人类监督.
持续的进化和谨慎的实施是最大限度地提高LLM的好处的关键,同时减轻医学中的风险.

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