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医疗系统的数字孪生体

Digital twin for healthcare systems.

作者信息

Vallée Alexandre

机构信息

Department of Epidemiology and Public Health, Foch Hospital, Suresnes, France.

出版信息

Front Digit Health. 2023 Sep 7;5:1253050. doi: 10.3389/fdgth.2023.1253050. eCollection 2023.

Abstract

Digital twin technology is revolutionizing healthcare systems by leveraging real-time data integration, advanced analytics, and virtual simulations to enhance patient care, enable predictive analytics, optimize clinical operations, and facilitate training and simulation. With the ability to gather and analyze a wealth of patient data from various sources, digital twins can offer personalized treatment plans based on individual characteristics, medical history, and real-time physiological data. Predictive analytics and preventive interventions are made possible by machine learning algorithms, allowing for early detection of health risks and proactive interventions. Digital twins can optimize clinical operations by analyzing workflows and resource allocation, leading to streamlined processes and improved patient care. Moreover, digital twins can provide a safe and realistic environment for healthcare professionals to enhance their skills and practice complex procedures. The implementation of digital twin technology in healthcare has the potential to significantly improve patient outcomes, enhance patient safety, and drive innovation in the healthcare industry.

摘要

数字孪生技术正在彻底改变医疗保健系统,它通过利用实时数据集成、先进分析和虚拟模拟来提升患者护理水平、实现预测性分析、优化临床操作,并促进培训与模拟。凭借从各种来源收集和分析大量患者数据的能力,数字孪生可以根据个体特征、病史和实时生理数据提供个性化治疗方案。机器学习算法使预测性分析和预防性干预成为可能,从而能够早期发现健康风险并进行积极干预。数字孪生可以通过分析工作流程和资源分配来优化临床操作,从而实现流程简化和患者护理改善。此外,数字孪生可以为医疗保健专业人员提供一个安全且逼真的环境,以提高他们的技能并练习复杂的程序。数字孪生技术在医疗保健领域的应用有可能显著改善患者治疗效果、提高患者安全性,并推动医疗行业的创新。

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