大型语言模型:入门指南和肠胃病学应用。

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
ACS Applied Electronic Materials Pub Date : 2024-02-22 eCollection Date: 2024-01-01 DOI:10.1177/17562848241227031
Omer Shahab, Bara El Kurdi, Aasma Shaukat, Girish Nadkarni, Ali Soroush
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引用次数: 0

摘要

在过去的一年中,ChatGPT 等工具中最先进的大型语言模型(LLM)的出现推动了人工智能(AI)创新的快速发展。这些功能强大的人工智能模型可以为指令和问题生成量身定制的高质量文本回复,而不需要耗费大量人力的特定任务训练数据或复杂的软件工程。随着技术的不断成熟,LLM 在改变临床工作流程、提高患者疗效、改善医学教育和优化医学研究方面具有巨大的潜力。在这篇综述中,我们将针对消化科医生对 LLM 进行实用的讨论。我们重点介绍了 LLM 的技术基础,强调了它们的主要优势和局限性,以及如何安全有效地与它们互动。我们讨论了 LLM 在临床胃肠病学实践、教育和研究中的一些潜在用例。最后,我们回顾了实施过程中的关键障碍以及为解决这些问题正在开展的工作。本综述旨在让胃肠病学家对 LLM 有一个基本的了解,以促进临床医生在这一快速新兴技术的开发和实施中发挥更积极的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Large language models: a primer and gastroenterology applications.

Over the past year, the emergence of state-of-the-art large language models (LLMs) in tools like ChatGPT has ushered in a rapid acceleration in artificial intelligence (AI) innovation. These powerful AI models can generate tailored and high-quality text responses to instructions and questions without the need for labor-intensive task-specific training data or complex software engineering. As the technology continues to mature, LLMs hold immense potential for transforming clinical workflows, enhancing patient outcomes, improving medical education, and optimizing medical research. In this review, we provide a practical discussion of LLMs, tailored to gastroenterologists. We highlight the technical foundations of LLMs, emphasizing their key strengths and limitations as well as how to interact with them safely and effectively. We discuss some potential LLM use cases for clinical gastroenterology practice, education, and research. Finally, we review critical barriers to implementation and ongoing work to address these issues. This review aims to equip gastroenterologists with a foundational understanding of LLMs to facilitate a more active clinician role in the development and implementation of this rapidly emerging technology.

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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
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