Practical Applications of Large Language Models for Health Care Professionals and Scientists

被引:0
|
作者
Reis, Florian [1 ]
Lenz, Christian [1 ]
Gossen, Manfred [2 ,3 ]
Volk, Hans-Dieter [4 ,5 ,6 ,7 ]
Drzeniek, Norman Michael [4 ,5 ,6 ,7 ]
机构
[1] Pfizer Pharm GmbH, Med Affairs, Berlin, Germany
[2] Helmholtz Zent Hereon, Inst Act Polymers, Teltow, Germany
[3] Berlin Brandenburg Ctr Regenerat Therapies BCRT, Berlin, Germany
[4] Charite Univ Med Berlin, Inst Med Immunol, Berlin, Germany
[5] Free Univ Berlin, Berlin, Germany
[6] Humboldt Univ, Berlin, Germany
[7] Charite Univ Med Berlin, Berlin Inst Hlth, BIH Ctr Regenerat Therapies BCRT, Augustenburger Pl 1, D-13353 Berlin, Germany
关键词
artificial intelligence; healthcare; chatGPT; large language model; prompting; LLM; applications; AI; scientists; physicians; health care;
D O I
10.2196/58478
中图分类号
R-058 [];
学科分类号
摘要
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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页数:9
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