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数字孪生在精准医疗应用中的研究进展和挑战
陈玉倩1,2,侯晓慧2,朱碧帆2,金春林2,李芬2*
0
(1. 上海政法学院经济管理学院, 上海 201701;
2. 上海市卫生和健康发展研究中心(上海市医学科学技术情报研究所)卫生政策研究部, 上海 200040
*通信作者)
摘要:
近年来,数字孪生作为新兴的人工智能技术为精准医疗的发展前景提供了更多可能性。数字孪生技术可以综合利用物体的全方位数据信息构建虚拟实体,通过在实体与虚拟体之间构建动态连接,提高模型分类、预测的准确性。目前,数字孪生在精准医疗领域的应用不仅包括治疗难度较大的专科疾病,也包括全生命周期、全人群层面的健康管理。但这些应用大多停留于技术模型的设计及利用单中心数据的验证层面,更多潜在的应用价值有待开发。本文对数字孪生在精准医疗应用中的研究进展和挑战进行归纳综述,为进一步突破技术瓶颈、拓宽应用领域、加快应用落地、强化法律法规提供思路与方向。
关键词:  数字孪生  人工智能  精准医疗  智慧医疗
DOI:10.16781/j.CN31-2187/R.20220583
投稿时间:2022-07-13修订日期:2022-11-14
基金项目:国家自然科学基金青年基金(G040601).
Digital twin in precision medicine application: research progress and challenges
CHEN Yu-qian1,2,HOU Xiao-hui2,ZHU Bi-fan2,JIN Chun-lin2,LI Fen2*
(1. School of Economics and Management, Shanghai University of Political Science and Law, Shanghai 201701, China;
2. Department of Health Policy Research, Shanghai Health Development Research Center (Shanghai Medical Information Center), Shanghai 200040, China
*Corresponding author)
Abstract:
In recent years, digital twin as an emerging artificial intelligence technology has provided greater potential prospects for precision medicine. Digital twin can build virtual entities by using comprehensive data information of entities, and improve the accuracy of classification and prediction models through the dynamic connection between entities and virtual entities. At present, the application of digital twin in precision medicine not only includes the treatment of specialized diseases, but also includes the health management of entire life cycle of all population. However, most applications are at the stage of technical model design and the validation of single-center data, and greater potential value need to be developed. This paper summarizes the research progress and challenges of digital twin application in precision medicine, so as to provide directions for overcoming the technical bottleneck, expanding the application field, accelerating the implementation of application, and strengthening laws and regulations.
Key words:  digital twin  artificial intelligence  precision medicine  smart healthcare