脊椎外科手术中的语言模型和处理系统的当前趋势和未来前景 - 范围审查
Vivek Sanker1, Emil O R Nordin2, Philip Heesen3
1Department of Neurosurgery, Stanford University, Palo Alto, CA, USA. vsanker@stanford.edu.
Neurosurgical review
|September 5, 2025
概括
自然语言处理 (NLP) 和大型语言模型 (LLM) 在脊椎外科手术中展现出有前途的效果, 然而,由于过度自信和遵守差距等局限性,需要谨慎执行.
科学领域:
- 医学的人工智能
- 脊椎手术的应用
- 自然语言处理 (NLP) 和大型语言模型 (LLM)
背景情况:
- 人工智能 (AI),特别是自然语言处理 (NLP) 和大型语言模型 (LLM),如ChatGPT,正在迅速发展.
- 这些人工智能技术为整合到各种医疗领域,包括专门的外科领域提供了显著的潜力.
- 在脊椎手术中NLP和LLM的应用是一个新兴的领域,趋势和前景不断变化.
研究的目的:
- 审查目前的NLP和LLM在脊椎外科手术中的趋势和前景.
- 评估这些人工智能工具在现场的潜在好处,应用和局限性.
- 提供关于人工智能在脊柱实践中的未来发展和实施的见解.
主要方法:
- 对英语文学进行了全面的叙事审查.
- 在PubMed,EMBASE,Web of Science和Scopus进行了搜索,截至2025年6月16日.
- 关键词包括"LLM"",自然语言处理"和"脊柱手术";从221个初始记录中包含了37项相关研究.
主要成果:
- 用于临床决策 (8项研究),患者咨询 (7),分类 (2) 和研究 (1).
- 在分类 (12项研究),临床决策 (3),患者咨询 (1),术后阿片类药物监测 (2) 和研究注册表 (1) 中使用NLP.
- 与GPT-3. 5相比,ChatGPT-4在临床建议中的准确性更高 (高达92%),幻觉减少.
结论:
- NLP和LLM具有影响脊椎手术实践的巨大潜力.
- 诸如过度自信的输出,遵循指导方针的差距和可读性问题等限制需要谨慎实施.
- 未来的研究应该专注于提高模型的准确性,促进合作,解决伦理问题,特别是人工智能幻觉.
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