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<p>With the accelerated application of artificial intelligence (AI) in healthcare, major economies have issued policies to regulate and guide its development, yet their policy orientations diverge due to differences in institutional culture, technological capacity, and development stage. To reveal trends in global healthcare AI policies, this research conducts a comparative topic modeling analysis. First, the research uses healthcare AI policies of China, the United States (U.S.), and the European Union (EU) from 2016 to 2025 as data sources, and constructs a policy corpus after preprocessing. Second, the research employs the BERTopic model for topic mining, clustering, and temporal evolution analysis. Findings reveal that over the past decade, the three economies have pursued different policy directions in tech orientation, data governance, ethical regulation, and service scenarios. China emphasizes application breadth and infrastructure development; the U.S. prioritizes institutional coordination and practical feasibility; the EU underscores risk governance and regulatory frameworks. This research reveals the policy governance trends and evolutionary trajectories of the three economies, providing theoretical support and methodological references for building a diversified and mutually beneficial international AI policy system in healthcare.</p>

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A comparative topic modeling analysis of AI policies in healthcare: insights from China, the United States, and the European Union

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月14日

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  • Pu Han,
  • Wuyi Qian,
  • Sengling Liu,
  • Wei Wang,
  • Xin Zheng,
  • Shenqi Jing

摘要

With the accelerated application of artificial intelligence (AI) in healthcare, major economies have issued policies to regulate and guide its development, yet their policy orientations diverge due to differences in institutional culture, technological capacity, and development stage. To reveal trends in global healthcare AI policies, this research conducts a comparative topic modeling analysis. First, the research uses healthcare AI policies of China, the United States (U.S.), and the European Union (EU) from 2016 to 2025 as data sources, and constructs a policy corpus after preprocessing. Second, the research employs the BERTopic model for topic mining, clustering, and temporal evolution analysis. Findings reveal that over the past decade, the three economies have pursued different policy directions in tech orientation, data governance, ethical regulation, and service scenarios. China emphasizes application breadth and infrastructure development; the U.S. prioritizes institutional coordination and practical feasibility; the EU underscores risk governance and regulatory frameworks. This research reveals the policy governance trends and evolutionary trajectories of the three economies, providing theoretical support and methodological references for building a diversified and mutually beneficial international AI policy system in healthcare.