The (Heart and) Soul of a Human Creation: Designing Echocardiography for the Big Data Age.
The (Heart and) Soul of a Human Creation: Designing Echocardiography for the Big Data Age.
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人类创造的（心和）灵魂：为大数据时代设计超声心动图。
DOI：
10.1016/j.echo.2023.04.016
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Abraham,Theodore
中科院分区：
文献类型：
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作者：
Arnaout,Rima;Hahn,RebeccaT;Hung,JudyW;Jone,Pei-Ni;Lester,StevenJ;Little,StephenH;Mackensen,GBurkhard;Rigolin,Vera;Sachdev,Vandana;Saric,Muhamed;Sengupta,ParthoP;Strom,JordanB;Taub,CynthiaC;Thamman,Ritu;Abraham,Theodore
机器学习（ML）和大数据有可能彻底改变心血管成像。1在超声心动图中，ML已用于图像增强、视图分类和引导、腔室量化甚至诊断。无论有没有机器学习，大数据分析都可以为日益可扩展的成果研究和质量改进提供动力。机器学习性能与其训练和测试的数据密不可分。1，2此外，高效和有效的数据存储和组织可以为医院系统和患者护理带来显著好处。3然而，传统的超声心动图图像存档和通信系统（Echo-PACS）并没有设计成利用临床成像和相关元数据进行大数据分析。从历史上看，超声心动图数据设计仅在其支持日常临床操作的情况下被考虑。随着对跨机构快速和大规模访问超声心动图数据的需求增加，当前的数据设计福尔斯短得不可接受。
Machine learning (ML) and big data hold the potential to revolutionize cardiovascular imaging. 1 In echocardiography, ML has been used for image enhancement, view classification and guidance, chamber quantification, and even diagnosis. With or without ML, big data analytics can power increasingly scalable outcomes research and quality improvement.Machine-learning performance is inextricably linked to the data it is trained and tested on. 1, 2 Furthermore, efficient and effective data storage and organization can have significant benefits to hospital systems and patient care. 3 However, legacy echocardiography picture archiving and communication systems (Echo-PACS) are not designed to leverage clinical imaging and related metadata for big data analytics. Historically, echocardiogram data design was considered only in as much as it supported day-to-day clinical operations. With increased need to access echocardiographic data quickly and at large scale across institutions, current data design falls unacceptably short.