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基于证据的医学人工智能学习策略。

Evidence-Based Learning Strategies in Medicine Using AI.

机构信息

Centro de Investigaciones Clínicas, Fundación Valle del Lili, Cali, Colombia.

Departamento de Anestesiología, Fundación Valle del Lili, Cali, Colombia.

出版信息

JMIR Med Educ. 2024 May 24;10:e54507. doi: 10.2196/54507.

Abstract

Large language models (LLMs), like ChatGPT, are transforming the landscape of medical education. They offer a vast range of applications, such as tutoring (personalized learning), patient simulation, generation of examination questions, and streamlined access to information. The rapid advancement of medical knowledge and the need for personalized learning underscore the relevance and timeliness of exploring innovative strategies for integrating artificial intelligence (AI) into medical education. In this paper, we propose coupling evidence-based learning strategies, such as active recall and memory cues, with AI to optimize learning. These strategies include the generation of tests, mnemonics, and visual cues.

摘要

大型语言模型(LLMs),如 ChatGPT,正在改变医学教育的格局。它们提供了广泛的应用,如辅导(个性化学习)、患者模拟、考试问题生成和信息的简化获取。医学知识的快速发展和个性化学习的需求突出了探索将人工智能(AI)融入医学教育的创新策略的相关性和及时性。在本文中,我们提出将基于证据的学习策略(如主动回忆和记忆线索)与 AI 相结合,以优化学习。这些策略包括生成测试、记忆技巧和视觉线索。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec50/11144835/236f1c0a9915/mededu-v10-e54507-g001.jpg

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