Regulatory Insights From 27 Years of Artificial Intelligence/Machine Learning-Enabled Medical Device Recalls in the United States: Implications for Future Governance.

Journal: JMIR medical informatics
Published Date: Jul 11, 2025

Abstract

BACKGROUND: Artificial intelligence/machine learning (AI/ML) has revolutionized the health care industry, particularly in the development and use of medical devices. The US Food and Drug Administration (FDA) has authorized over 878 AI/ML-enabled medical devices, reflecting a growing trend in both quantity and application scope. Understanding the distinct challenges these devices present in terms of FDA regulation violations is crucial for effectively avoiding recalls. This is particularly pertinent for proactive measures regarding medical devices.

Authors

  • Wei-Pin Chen
    Department of Biomedical Engineering, National Cheng Kung University, No.138, Shengli Rd, North District, Tainan, 701, Taiwan, 886 2757575 ext 63438.
  • Wei-Guang Teng
    Department of Engineering Science, National Cheng Kung University, Tainan, Taiwan.
  • C Benson Kuo
    Department of Regulatory and Quality Sciences, University of Southern California, Los Angeles, CA, 90033, United States.
  • Yu-Jui Yen
    Department of Engineering Science, National Cheng Kung University, Tainan, Taiwan.
  • Jian-Yu Lian
    Department of Biomedical Engineering, National Cheng Kung University, No.138, Shengli Rd, North District, Tainan, 701, Taiwan, 886 2757575 ext 63438.
  • Matthew Sing
    Department of Biomedical Engineering, National Cheng Kung University, No.138, Shengli Rd, North District, Tainan, 701, Taiwan, 886 2757575 ext 63438.
  • Peng-Ting Chen
    Department of Biomedical Engineering, National Cheng Kung University, No.138, Shengli Rd, North District, Tainan, 701, Taiwan, 886 2757575 ext 63438.

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