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聊天GPT,巴德和生物医学研究的大型语言模型:机遇和陷

Surendrabikram Thapa¹, Surabhi Adhikari²

¹Virginia Tech, Blacksburg, VA, 24060, USA. surendrabikram@vt.edu.

Annals of biomedical engineering

|June 16, 2023

概括

大型语言模型 (LLM) 为生物医学研究提供了强大的工具,有助于文学评论和假设生成. 仔细验证至关重要,以减轻与这些先进的人工智能技术相关的错误信息风险.

科学领域:

生物医学工程生物医学工程
人工智能在医学中的应用
科学研究工具科学研究工具

背景情况:

像ChatGPT和Bard这样的大型语言模型 (LLM) 正在改变科学研究.
在生物医学研究中,LLM既有显著的机遇,也存在潜在的陷.

研究的目的:

为生物医学研究中的LLM提供全面的概述.
探索实施法学士的机会和挑战.
为负责任和有效的LLM利用提供策略.

主要方法:

审查生物医学研究当前的LLM应用.
对潜在益处的分析,包括文献审查和假设生成.
识别风险,如错误信息和需要验证.

主要成果:

法律法规可以简化诸如文献总结和复杂数据分析等任务.
士课程有助于产生新的研究假设.
错误信息和严格核查的需要是关键的挑战.

结论:

士课程具有巨大的潜力,可以促进生物医学研究和工程.
负责任的实施需要强大的验证和验证策略.
解决LLM的局限性对于最大限度地提高它们在科学中的实用性至关重要.

关键词:

巴尔德巴尔德巴尔德巴尔德是什么意思生物医学研究的研究.聊天GPT 聊天GPT 聊天大型语言模型.自然语言处理自然语言处理.

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