面向医疗保健专业人员和科学家的大型语言模型的实际应用。

IF 3.1 3区 医学 Q2 MEDICAL INFORMATICS
Florian Reis, Christian Lenz, Manfred Gossen, Hans-Dieter Volk, Norman Michael Drzeniek
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引用次数: 0

摘要

无标签:随着大型语言模型(LLMs)的普及,在医疗保健和研究中有效、安全地使用这些模型的策略变得越来越重要。尽管医疗保健专业人员和科学家对利用 LLMs 的潜力越来越感兴趣和渴望,但由于缺乏用户经验,最初的尝试可能会产生不理想的结果,从而使人工智能(AI)工具与日常工作的整合变得更加复杂。这篇文章的观点聚焦于具有有限 LLM 经验的科学家和医疗保健专业人员,重点介绍并讨论了 6 个易于实施的实用案例。这些案例包括定制翻译、完善文本和提取信息、生成全面概述和专业见解、将观点编译成连贯的叙述、制作个性化教育材料,以及促进智力比拼。此外,我们还讨论了在生物医学中实施人工智能工具的一般提示策略和注意事项。尽管存在各种障碍和挑战,但将 LLM 融入医生和研究人员的日常工作有望提高工作场所的生产力和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Practical Applications of Large Language Models for Health Care Professionals and Scientists.

Unlabelled: With the popularization of large language models (LLMs), strategies for their effective and safe usage in health care and research have become increasingly pertinent. Despite the growing interest and eagerness among health care professionals and scientists to exploit the potential of LLMs, initial attempts may yield suboptimal results due to a lack of user experience, thus complicating the integration of artificial intelligence (AI) tools into workplace routine. Focusing on scientists and health care professionals with limited LLM experience, this viewpoint article highlights and discusses 6 easy-to-implement use cases of practical relevance. These encompass customizing translations, refining text and extracting information, generating comprehensive overviews and specialized insights, compiling ideas into cohesive narratives, crafting personalized educational materials, and facilitating intellectual sparring. Additionally, we discuss general prompting strategies and precautions for the implementation of AI tools in biomedicine. Despite various hurdles and challenges, the integration of LLMs into daily routines of physicians and researchers promises heightened workplace productivity and efficiency.

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来源期刊
JMIR Medical Informatics
JMIR Medical Informatics Medicine-Health Informatics
CiteScore
7.90
自引率
3.10%
发文量
173
审稿时长
12 weeks
期刊介绍: JMIR Medical Informatics (JMI, ISSN 2291-9694) is a top-rated, tier A journal which focuses on clinical informatics, big data in health and health care, decision support for health professionals, electronic health records, ehealth infrastructures and implementation. It has a focus on applied, translational research, with a broad readership including clinicians, CIOs, engineers, industry and health informatics professionals. Published by JMIR Publications, publisher of the Journal of Medical Internet Research (JMIR), the leading eHealth/mHealth journal (Impact Factor 2016: 5.175), JMIR Med Inform has a slightly different scope (emphasizing more on applications for clinicians and health professionals rather than consumers/citizens, which is the focus of JMIR), publishes even faster, and also allows papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research.
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