医学人工智能研究伦理审查实施路径探析-基于算法透明和数据安全维度

      Exploration of the Implementation Path of Ethical Review in Medical Artificial Intelligence Research - Based on Algorithm Transparency and Data Security Dimensions

      • 摘要:
        目的 基于算法透明和数据安全的维度,建立一套切实可行的医学人工智能研究伦理审查机制,有效保障研究参与者的生命健康、人格尊严及合法权益。
        方法 梳理国内外医学人工智能研究伦理审查的依据,分析相关伦理审查实践中存在的问题和难点,结合工作实际,探讨医学人工智能研究伦理审查的程序和要点。
        结果 明确了医学人工智能研究的伦理审查需要加强跨学科合作,邀请软件工程、计算机科学等多领域的专家共同参与审查工作,优化伦理申请与受理的流程,规范伦理审查的方式,并结合医学人工智能研究不同类型,制定相应的审查要点,重点关注研究风险受益比的评估和知情同意程序的规范化程度。
        结论 本研究在遵循传统伦理审查基本要求的同时,结合人工智能技术的特殊性,提出了规范有效的医学人工智能研究伦理审查的实施路径,可操作性较强。

         

        Abstract: Objective To establish a practical and feasible ethical review mechanism for medical artificial intelligence research, effectively safeguarding the life, health, personal dignity, and legitimate rights and interests of research participants. Methods To sort out the basis for ethical review of medical artificial intelligence research at home and abroad, analyze the problems and difficulties in relevant ethical review practices, and explore the procedures and key points of ethical review of medical artificial intelligence research based on practical work. Results It has been clarified that the ethical review of medical artificial intelligence research needs to strengthen interdisciplinary cooperation, invite experts from multiple fields such as software engineering and computer science to participate in the review work, optimize the process of ethical application and acceptance, standardize the way of ethical review, and develop corresponding review points based on different types of medical artificial intelligence research, focusing on the evaluation of research risk benefit ratio and the standardization of informed consent procedures. Conclusion This study proposes a standardized and effective implementation path for ethical review of medical artificial intelligence research, while adhering to the basic requirements of traditional ethical review and taking into account the particularity of artificial intelligence technology. The implementation path is highly operable.

         

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