生成式人工智能:对生物医学和卫生专业教育的影响。

IF 7 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
William Hersh
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引用次数: 0

摘要

生成式人工智能(AI)对生物医学和健康产生了深远的影响,无论是在专业工作还是在教育方面。基于大型语言模型(llm),生成式人工智能已经被发现在模拟情况下表现得和人类一样好,比如参加医学委员会考试、回答临床问题、解决临床病例、应用临床推理和总结信息。生成式人工智能也被广泛应用于教育领域,在学术课程及其评估中表现出色。这篇综述总结了法学硕士的成功,并强调了他们在教育背景下面临的一些挑战,最明显的是可能会破坏专业工作知识和技能的获取。然后,它提供了最佳实践建议,以克服法学硕士在教育中使用的缺点。尽管在教育中使用生成式人工智能存在挑战,但生物医学和卫生等领域的所有学生和教师都必须理解并能够熟练使用人工智能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generative Artificial Intelligence: Implications for Biomedical and Health Professions Education.

Generative artificial intelligence (AI) has had a profound impact on biomedicine and health, both in professional work and in education. Based on large language models (LLMs), generative AI has been found to perform as well as humans in simulated situations taking medical board exams, answering clinical questions, solving clinical cases, applying clinical reasoning, and summarizing information. Generative AI is also being used widely in education, performing well in academic courses and their assessments. This review summarizes the successes of LLMs and highlights some of their challenges in the context of education, most notably aspects that may undermines the acquisition of knowledge and skills for professional work. It then provides recommendations for best practices to overcome the shortcomings of LLM use in education. Although there are challenges for the use of generative AI in education, all students and faculty, in biomedicine and health and beyond, must have understanding and be competent in its use.

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来源期刊
CiteScore
11.10
自引率
1.70%
发文量
0
期刊介绍: The Annual Review of Biomedical Data Science provides comprehensive expert reviews in biomedical data science, focusing on advanced methods to store, retrieve, analyze, and organize biomedical data and knowledge. The scope of the journal encompasses informatics, computational, artificial intelligence (AI), and statistical approaches to biomedical data, including the sub-fields of bioinformatics, computational biology, biomedical informatics, clinical and clinical research informatics, biostatistics, and imaging informatics. The mission of the journal is to identify both emerging and established areas of biomedical data science, and the leaders in these fields.
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