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<p>This study aimed to analyze the evolution of scientific production on AI applied to medical imaging, focusing on temporal trends, the global distribution of research, and trends in clinical applications. A bibliometric study was conducted using the Scopus and Web of Science databases, including publications from 2020 to 2025. Original studies addressing AI applications in radiography, computed tomography, magnetic resonance imaging, and mammography were included. Data was analyzed using R and VOSviewer to assess publication trends and the temporal evolution of author keywords based on their annual frequency. A significant increase in scientific production was observed, indicating expansion of the field. In contrast, citation trends showed no statistically significant temporal change. Research output was geographically concentrated in high-income countries, particularly China and the United States. Thematic analysis revealed a shift from methodological development to clinically oriented applications, with oncology emerging as the primary domain, followed by pulmonary and neurological diseases. More recent diversification into additional clinical areas was also identified. Scientific production increasingly reflects a focus on clinically oriented applications. However, challenges related to generalizability, equity, and real-world validation remain. Future efforts should prioritize multicenter validation, standardization, and context-adapted implementation strategies to ensure equitable and effective adoption across diverse healthcare settings.</p>

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Global trends in artificial intelligence applications in medical imaging and implications for clinical practice

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年8月4日

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  • Maria Fernanda Buge Figueredo,
  • Nathally de Paula da Cunha Alves,
  • Wevellyn Lunara Sousa Miranda,
  • Diego Simeone

摘要

This study aimed to analyze the evolution of scientific production on AI applied to medical imaging, focusing on temporal trends, the global distribution of research, and trends in clinical applications. A bibliometric study was conducted using the Scopus and Web of Science databases, including publications from 2020 to 2025. Original studies addressing AI applications in radiography, computed tomography, magnetic resonance imaging, and mammography were included. Data was analyzed using R and VOSviewer to assess publication trends and the temporal evolution of author keywords based on their annual frequency. A significant increase in scientific production was observed, indicating expansion of the field. In contrast, citation trends showed no statistically significant temporal change. Research output was geographically concentrated in high-income countries, particularly China and the United States. Thematic analysis revealed a shift from methodological development to clinically oriented applications, with oncology emerging as the primary domain, followed by pulmonary and neurological diseases. More recent diversification into additional clinical areas was also identified. Scientific production increasingly reflects a focus on clinically oriented applications. However, challenges related to generalizability, equity, and real-world validation remain. Future efforts should prioritize multicenter validation, standardization, and context-adapted implementation strategies to ensure equitable and effective adoption across diverse healthcare settings.