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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">JCER</journal-id><journal-title-group><journal-title>Journal of Contemporary Educational Research</journal-title></journal-title-group><issn>2208-8466</issn><eissn>2208-8474</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/jcer.v10i6.15451</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Application and Governance of Generative Artificial Intelligence in Clinical Teaching</title><url>https://artdesignp.com/journal/JCER/10/6/10.26689/jcer.v10i6.15451</url><author>YuShichao,MengFanzheng,WuHui,FuDongye,WangXinyu,GaoMan</author><pub-date pub-type="publication-year"><year>2026</year></pub-date><volume>10</volume><issue>6</issue><history><date date-type="pub"><published-time>2026-07-14</published-time></date></history><abstract>The iterative development of generative artificial intelligence (GenAI) and large language models has enabled them to support multiple aspects of clinical teaching at a functional level, including language support, virtual consultations, clinical reasoning and feedback support, skills simulation training, and writing and research assistance. This paper reviews the current status and evidence limitations of these typical application scenarios and proposes a GenAI governance model suitable for clinical teaching scenarios, considering the high-stakes nature of clinical teaching. Focusing on issues such as “hallucination” outputs and factual deviations, over-reliance, academic integrity, privacy, and data security, this paper proposes governance recommendations centered on clarifying responsibility boundaries and retaining key evidence. 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