[医学教育和人工智能:观点和伦理挑战]。

Omar Chávez-Martínez, Leonardo Adriano Ragacini
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引用次数: 0

摘要

人工智能(AI)通过实现个性化学习、即时反馈和临床模拟,推动医学教育的创新。然而,它引发了诸如人类技能丧失、错误信息和道德问题等担忧。ChatGPT因其自然语言生成能力而获得了突出的地位,尽管缺乏真正的理解。本文的目的是分析人工智能,特别是ChatGPT在医学教育中的应用,确定其好处、局限性和伦理影响,这就是为什么通过PubMed(2020-2025)的系统搜索进行定性综合评价的原因,使用与人工智能和医学教育相关的MeSH描述符。共收录了37篇开放获取的英文全文文章。使用主题方法对信息进行分析和综合,分为四类:教学应用、益处、挑战和伦理建议,因此我们得到了这些结果:人工智能支持临床模拟、个性化学习和公平获取。其好处包括增强临床推理和自主学习能力。挑战依然存在,如偏见、数据隐私和错误信息。本文提出了集成的五大支柱,并将其分为消费者、翻译人员和开发人员。数字管理成为确保质量和可靠性的关键因素。我们的结论是,如果以道德、批判性和以人为本的方式实施,人工智能可以改变医学教育。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

[Medical education and artificial intelligence: perspectives and ethical challenges].

[Medical education and artificial intelligence: perspectives and ethical challenges].

Artificial intelligence (AI) drives innovation in medical education by enabling personalized learning, instant feedback, and clinical simulations. However, it raises concerns such as loss of human skills, misinformation, and ethical issues. ChatGPT has gained prominence for its natural language generation capabilities, despite lacking real understanding. The aim of this article was to analyze the use of AI, particularly ChatGPT, in medical education, identifying its benefits, limitations, and ethical implications, which is why a qualitative integrative review was conducted through a systematic search in PubMed (2020-2025), using MeSH descriptors related to artificial intelligence and medical education. A total of 37 open-access, full-text articles in English were included. The information was analyzed and synthesized using a thematic approach, organized into 4 categories: pedagogical applications, benefits, challenges, and ethical recommendations, thanks to which we had these results: AI supports clinical simulations, personalized learning, and equitable access. Benefits include enhanced clinical reasoning and autonomous learning. Challenges remain, such as bias, data privacy, and misinformation. Five pillars for integration are proposed, along with a professional classification into consumers, translators, and developers. Digital curation emerges as a key element to ensure quality and reliability. We conclude that AI can transform medical education if implemented ethically, critically, and with a human-centered approach.

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