Kim Eun Man, Lim Yooseok
Department of Nursing Science, Sun Moon University, Asan, Republic of Korea.
Office of Hospital Information, Seoul National University Hospital, Seoul, Republic of Korea.
Sci Rep. 2025 Aug 28;15(1):31734. doi: 10.1038/s41598-025-17517-w.
Digital twin (DT) technology is revolutionizing healthcare systems by leveraging real-time data integration and advanced analytics to enhance patient care, optimize clinical operations, and facilitate simulation. This study aimed to identify key research trends related to the application of DTs to healthcare using structural topic modeling (STM). Five electronic databases were searched for articles related to healthcare and DT. Using the held-out likelihood, residual, semantic coherence, and lower bound as metrics revealed that the optimal number of topics was eight. The "security solutions to improve data processes and communication in healthcare" topic was positioned at the center of the network and connected to multiple nodes. The "cloud computing and data network architecture" and "machine-learning algorithms for accurate detection and prediction" topics served as a bridge between technical and healthcare topics, suggesting their high potential for use in various fields. The widespread adoption of DTs in healthcare requires robust governance structures to protect individual rights, ensure data security and privacy, and promote transparency and fairness. Compliance with regulatory frameworks, ethical guidelines, and a commitment to accountability are also crucial.
数字孪生（DT）技术正在通过利用实时数据集成和先进分析来变革医疗保健系统，以提高患者护理水平、优化临床运营并促进模拟。本研究旨在使用结构主题模型（STM）确定与DT在医疗保健中的应用相关的关键研究趋势。在五个电子数据库中搜索了与医疗保健和DT相关的文章。使用留出似然度、残差、语义连贯度和下限作为指标表明，最佳主题数量为八个。“改善医疗保健中数据流程和通信的安全解决方案”主题位于网络中心并与多个节点相连。“云计算和数据网络架构”以及“用于准确检测和预测的机器学习算法”主题充当了技术与医疗保健主题之间的桥梁，表明它们在各个领域具有很高的应用潜力。DT在医疗保健中的广泛采用需要强大的治理结构来保护个人权利、确保数据安全和隐私，并促进透明度和公平性。遵守监管框架、道德准则以及对问责制的承诺也至关重要。
