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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Masumeh Saeidi</PublisherName>
				<JournalTitle>Medical Education Bulletin</JournalTitle>
				<Issn>2783-1809</Issn>
				<Volume>7</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2026</Year>
					<Month>06</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Preserving Clinical Reasoning in the Age of AI-Assisted Medical Education</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>1177</FirstPage>
			<LastPage>1179</LastPage>
			<ELocationID EIdType="pii">246198</ELocationID>
			
<ELocationID EIdType="doi">10.22034/meb.2026.588440.1132</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Amer</FirstName>
					<LastName>Yazdanparast</LastName>
<Affiliation>Associate Professor of Pediatric Cardiology, Department of Pediatrics, Faculty of Medicine, Bushehr University of Medical Sciences, Bushehr, Iran.</Affiliation>
<Identifier Source="ORCID">0000-0001-7307-4420</Identifier>

</Author>
<Author>
					<FirstName>Abbas</FirstName>
					<LastName>Bahreini</LastName>
<Affiliation>MD, Shiraz University of Medical Sciences, Shiraz, Iran.</Affiliation>
<Identifier Source="ORCID">0000-0003-4218-7523</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2026</Year>
					<Month>06</Month>
					<Day>24</Day>
				</PubDate>
			</History>
		<Abstract>Artificial intelligence (AI) is rapidly transforming medical education by enabling personalized learning, rapid knowledge retrieval, and automated academic support. While these technologies offer substantial benefits, their growing use raises concerns about cognitive over-reliance and the potential erosion of independent clinical reasoning among medical students. AI systems can produce fluent and persuasive outputs even when inaccuracies or reasoning errors are present, potentially fostering misplaced confidence if learners are not trained to critically appraise such information. This letter examines the risks associated with excessive dependence on AI in medical training and emphasizes the need to integrate these tools within pedagogical frameworks that prioritize critical evaluation and verification. Preserving independent diagnostic judgment alongside responsible AI adoption is essential to ensuring safe and effective future clinical practice.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Artificial intelligence, Automation bias</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">AI literacy, Clinical reasoning</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">medical education</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://www.medicaleducation-bulletin.ir/article_246198_9284a7a06152ea1618a55e2f8526940c.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
