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适用于心力衰竭患者的应用程序和在线平台。

Apps and Online Platforms for Patients with Heart Failure.

作者信息

Ahmed Nida, Ahmed Sabahat, Grapsa Julia

机构信息

Cardiology Department, Barts Heart Centre, St Bartholomew's Hospital London, UK.

GKT School of Medical Education, King's College London London, UK.

出版信息

Card Fail Rev. 2020 May 25;6:e14. doi: 10.15420/cfr.2019.15. eCollection 2020 Mar.

DOI:10.15420/cfr.2019.15
PMID:32537247
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7277783/
Abstract

The use of the internet for health advice and information has burgeoned over recent years. This corresponds with an increasing number of people living with heart failure and, in the context of a greater focus on patient engagement, producing accurate online health information is becoming vitally important. To help meet this need, major cardiology societies have designed dedicated, patient-specific areas on their websites. This article aims to provide an overview of the patient information resources from three main professional societies: the European Society of Cardiology, American Heart Association and American College of Cardiology. A summary of the content of these dedicated websites and two smartphone apps is provided, along with a brief look into the future role of these technologies and resources in supporting both patients and their clinicians in the management of heart failure.

摘要

近年来,利用互联网获取健康建议和信息的情况迅速发展。这与心力衰竭患者人数的增加相呼应,并且在更加注重患者参与的背景下,提供准确的在线健康信息变得至关重要。为满足这一需求,主要的心脏病学学会在其网站上设计了专门针对患者的区域。本文旨在概述三个主要专业学会(欧洲心脏病学会、美国心脏协会和美国心脏病学会)提供的患者信息资源。提供了这些专门网站和两款智能手机应用程序内容的总结,同时简要探讨了这些技术和资源在支持患者及其临床医生管理心力衰竭方面未来的作用。

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Prediction of 30-Day All-Cause Readmissions in Patients Hospitalized for Heart Failure: Comparison of Machine Learning and Other Statistical Approaches.预测因心力衰竭住院患者的 30 天全因再入院率:机器学习与其他统计学方法的比较。
JAMA Cardiol. 2017 Feb 1;2(2):204-209. doi: 10.1001/jamacardio.2016.3956.
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Using recurrent neural network models for early detection of heart failure onset.使用循环神经网络模型进行心力衰竭发作的早期检测。
J Am Med Inform Assoc. 2017 Mar 1;24(2):361-370. doi: 10.1093/jamia/ocw112.
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Analysis of online information searching for cardiovascular diseases on a consumer health information portal.在一个消费者健康信息门户网站上对心血管疾病在线信息搜索情况的分析。
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