Environment scan of generative AI infrastructure for clinical and translational science

作者：Betina Idnay, Zihan Xu, William G. Adams, Mohammad Adibuzzaman, Nicholas R. Anderson, Neil Bahroos, Douglas S. Bell, Cody Bumgardner, Thomas R. Campion, Mario Castro, James J. Cimino, I. Glenn Cohen, David A Dorr, Peter L. Elkin, Jungwei Fan, Todd Ferris, David J. Foran, David Hanauer, Mike Hogarth, Kun Huang, Jayashree Kalpathy-Cramer, Manoj Kandpal, Niranjan S. Karnik, Avnish Katoch, Albert M. Lai, Christophe Lambert, Lang Li, Christopher J. Lindsell, Jinze Liu, Zhiyong Lu, Yuan Luo, Peter B. McGarvey, Eneida A. Mendonça, Parsa Mirhaji, Shawn N. Murphy, John D. Osborne, Ioannis Ch. Paschalidis, Paul A. Harris, Fred Prior, Nicholas J. Shaheen, Nawar Shara, Ida Sim, Umberto Tachinardi, Lemuel R. Waitman, Rosalind J. Wright, Adrian Zai, Kai Zheng, Sandra Soo‐Jin Lee, Bradley Malin, Karthik Natarajan, W. Nicholson Price, Rui Zhang, Yiye Zhang, Hua Xu, Jiang Bian, Chunhua Weng, Yifan Peng · 发表于：npj Health Systems · 年份：2025 · DOI：10.1038/s44401-024-00009-w · 被引用次数：9 · 研究领域：Artificial Intelligence in Healthcare and Education、Biomedical and Engineering Education、Ethics in Clinical Research

This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 institutions supported by the CTSA Program led by the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH) at the United States. Key findings indicate a diverse range of institutional strategies, with most organizations in the experimental phase of GenAI deployment. The results underscore the need for a more coordinated approach to GenAI governance, emphasizing collaboration among senior leaders, clinicians, information technology staff, and researchers. Our analysis reveals that 53% of institutions identified data security as a primary concern, followed by lack of clinician trust (50%) and AI bias (44%), which must be addressed to ensure the ethical and effective implementation of GenAI technologies.