Advancements in Clinical Evaluation and Regulatory Frameworks for AI-Driven Software as a Medical Device (SaMD)

被引:0
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作者
Yang, Shiau-Ru [1 ]
Chien, Jen-Tzung [1 ]
Lee, Chen-Yi [1 ]
机构
[1] National Yang Ming Chiao Tung University, Institute of Electrical and Computer Engineering, Hsinchu,30010, Taiwan
关键词
D O I
10.1109/OJEMB.2024.3485534
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摘要
Owing to the rapid progress in artificial intelligence (AI) and the widespread use of generative learning, the problem of sparse data has been solved effectively in various research fields. The application of AI technologies has resulted in important transformations in healthcare, particularly in radiology. To ensure the high quality, safety, and effectiveness of AI and machine learning (ML) medical devices, the US Food and Drug Administration (FDA) has established regulatory guidelines to support the performance evaluation of medical devices. Furthermore, the FDA has proposed continuous surveillance requirements for AIML medical devices. This paper presents a summary of SaMD products that have passed the FDA 510 (k) AIML pathway, the challenges associated with the current AIML software-as-a-medical-device, and solutions for promoting the development of AI technologies in medicine. We hope to provide valuable information pertaining to medical-device design, development, and monitoring to ultimately achieve safer and more effective personalized medical services. © 2020 IEEE.
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页码:147 / 151
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