数智赋能医学科技的治理管理 (一)大数据和人工智能对医学的影响、挑战和潜在策略分析  

Governance and management for promoting science and techonolgy in medicine by digital and artificial intelligence(Ⅰ)Analysis of the impacts,challenges,and potential strategies for big data and AI in medicine

作　　者：关健[1] Guan Jian(National Population and Health Scientific Data Centre(Clinical center),Peking Union Medical College Hospital,Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC),Beijing 100730,China)

机构地区：[1]北京协和医学院&中国医学科学院,北京协和医院,国家人口健康科学数据中心(临床医学),北京100730

出　　处：《中华医学科研管理杂志》2025年第1期1-7,共7页Chinese Journal of Medical Science Research Management

基　　金：北京协和医学院本科教育教学改革项目(2023zlgl 059);国家重点研发计划课题(2021YFC2302001)。

摘　　要：目的本研究旨在探讨影响医学大数据和人工智能的治理管理的重要因素及其引起的挑战与问题,为提出相应的解决方案提供依据。方法我们借鉴现有文献,简要分析大数据和人工智能对医学研究的影响。通过讨论分析影响数据治理管理的核心要素及其相互关系,提出一些潜在的策略,解决与医学大数据和人工智能相关的主要挑战与问题。结果大数据和人工智能的应用显著影响医学研究范式、药物研发、临床决策和医学教育。这些应用引起数据治理管理相关的挑战分为两个主要方面。第一涉及由技术核心因素引发的伦理挑战。其主要问题是在数据收集、编码和反馈这些算法过程可能存在的偏差。第二涉及数据和利益相关者两大治理管理要素,其主要问题是基础数据的质量和整合效率低下,以及数据产权和数据相关知识产权缺乏认可的认定体系,其在确定数据共享和应用期间在利益相关者之间的权益分配和责任归属方面至关重要。结论应解决医学中大数据和人工智能的治理和管理的关键问题。这些措施包括制定数据伦理框架,包括医学人工智能的伦理策略和要点;建立数据结构标准,以提高数据质量和交互性;以及明确关于数据所有权、知识产权及其权益分配的决策原则。ObjectiveThis study aimed to explore the challenges and issues arising from the factors that affect the governance and management of big data and artificial intelligence in medicine,and to establish a foundation for proposing solutions to these challenges and issues.MethodsWe analyzed how big data and artificial intelligence influence different aspects of medical research by reviewing a range of literature.We proposed potential strategies to address the major challenges and issues associated with medical big data and artificial intelligence by analyzing their core elements and interrelationships.ResultsThe application of big data and artificial intelligence has significantly impacted the paradigms of medical research,drug development,clinical decision-making,and medical education.Two main aspects highlighted the challenges and issues related to governance and management arising from these advancements.The first involved ethical challenges stemming from data and algorithmic processes,including those related to artificial intelligence.A major concern was the potential bias in the algorithms,which can emerge during data collection,coding,and feedback.The second aspect focused on the governance and management elements of the data and stakeholders.Two key issues were the quality and integration efficiency of fundamental data,as well as property rights and intellectual property related to data,which currently lack a proper recognition system.This recognition was vital for distributing rights,interests,and responsibilities among stakeholders during data sharing and applications.ConclusionKey issues regarding the governance and management of big data and artificial intelligence in medicine should be addressed.These include developing a framework for data ethics,including ethical review strategies and keypoints for medical artificial intelligence;establishing standards for data structure to enhance data quality and interactivity;and clarifying the principles of decisions on data ownership and intellectual property to dist

关 键 词：大数据 人工智能 医学研究 算法 生成性人工智能 数据治理 数据管理 数据伦理学 知识产权 解决方案 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]