大型语言模型的突破 医学应用的发布:1年时间表和前景
Marco Cascella1, Federico Semeraro2, Jonathan Montomoli3
1Anesthesia and Pain Medicine, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Via S. Allende, Baronissi, 84081, Italy.
Journal of medical systems
|February 17, 2024
概括
大型语言模型 (LLM) 在医疗保健中正在快速发展,用于记录和总结等任务. 未来的应用包括人工智能驱动的诊断支持和增强的患者参与工具.
科学领域:
- 自然语言处理 (NLP) 是一种自然语言处理.
- 人工智能在医学中的应用
- 生物医学信息学 生物医学信息学
背景情况:
- 大型语言模型 (LLM) 是通过大量文本数据进行训练的先进人工智能系统.
- 最近LLM版本的升级,其中许多适用于医疗保健.
- 保持与LLM演变的步伐,并了解他们的医疗应用是专业人士的挑战.
研究的目的:
- 提供最近发布的LLMs的概述.
- 突出LLMs的潜在医疗应用.
- 讨论未来在医学上安全有效地使用LLM的前景.
主要方法:
- 基于变压器的深度学习架构的审查.
- 对医疗保健应用程序 (如聊天机器人,虚拟助理) 的LLM定制的分析.
- 在临床文档,医学文献总结和患者互动中探索当前和新兴用途.
主要成果:
- 在临床文档,医学文献总结和面向患者的应用中,LLM显示出潜力.
- 在开发用于诊断支持,临床决策和患者分组的LLM方面仍然存在挑战.
- 预训练模型的定制正在推动医疗保健中对话性AI的快速发展.
结论:
- 在患者护理,研究和医学教育方面,LLM提供了巨大的潜力.
- 未来的LLM发展旨在提供支持临床决策和患者管理的多功能工具.
- 增强的虚拟临床合作伙伴可以改善患者参与和慢性疾病管理.
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