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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.v9i10.12676</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Transforming Medical Education: Cultivating Statistical Thinking in the AI Era</title><url>https://artdesignp.com/journal/JCER/9/10/10.26689/jcer.v9i10.12676</url><author>HuSonghua,YaoYingshui,TanJiao,ChenYan</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>9</volume><issue>10</issue><history><date date-type="pub"><published-time>2025-11-10</published-time></date></history><abstract>Artificial intelligence (AI) is rapidly transforming healthcare and medical education. Strong statistical thinking skills are vital for evaluating and applying AI tools. However, traditional medical statistics education has not adapted to this demand. This paper first analyzes the connotation and importance of statistical thinking, points out the significant challenges currently faced by medical statistics education, and then proposes strategies such as innovative teaching methods combined with evidence-based medicine, utilizing AI platforms for supplemental teaching, multidisciplinary integration, and strengthening the understanding of the statistical foundations of AI to enhance the statistical thinking abilities of medical professionals. 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