在大型语言模型时代的生物医学自然语言处理
Naoto Usuyama1, Cliff Wong1, Sheng Zhang1
1Microsoft Research, Redmond, Washington, USA;
Annual review of biomedical data science
|April 17, 2025
概括
大型语言模型 (LLM) 正在彻底改变生物医学自然语言处理 (NLP),提高患者的护理和发现. 解决诸如幻觉和安全等挑战是解锁AI的关键.
科学领域:
- 生物医学信息学是生物医学信息学.
- 人工智能的人工智能是人工智能.
- 自然语言处理自然语言处理.
背景情况:
- 生物医学已经经历了重大的数字化,从基因组测序到电子医疗记录.
- 大型语言模型 (LLM) 现在正在推动自然语言处理 (NLP) 的生成人工智能 (AI) 革命.
研究的目的:
- 审查生物医学NLP的挑战和机遇.
- 提供历史背景,调查当前的技术状况.
- 探索人工智能研究人员和生物医学从业者的未来前沿.
主要方法:
- 审查当前文学和生物医学NLP的新兴趋势.
- 分析LLM对医疗保健和生物医学发现的影响.
- 讨论包括幻觉,遗漏,合规性和安全性在内的挑战.
主要成果:
- 生物医学NLP自动化了知识提取和医学抽象等任务,提高了生产力.
- 新兴的人工智能方法承诺创造性收益,并使用大规模数据发现新的能力.
- 整合各种数据模式,如成像和基因组学,对于全面的解决方案至关重要.
结论:
- 法律学士学位为优化患者护理和加速生物医学发现提供了前所未有的可能性.
- 确保LLM合规性,安全性以及解决幻觉等局限性至关重要.
- 人工智能的整合,特别是LLMs,将改变生物医学研究和实践.
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